Selected Paper Awards & Personal Awards

For more awards, please browse our news section.

All Publications

  1. 2025

    1. D. Shi, Y. Wang, Y. Bai, A. Bulling, and A. Oulasvirta, “Chartist: Task-driven Eye Movement Control for Chart Reading,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, in Proceedings of the CHI Conference on Human Factors in Computing Systems. New York, NY, United States, May 2025, pp. 1–14. doi: 10.1145/3706598.3713128.
  2. 2024

    1. P. Gralka, C. Müller, M. Heinemann, G. Reina, D. Weiskopf, and T. Ertl, “Power Overwhelming: The One With the Oscilloscopes,” Journal of Visualization, Aug. 2024, doi: 10.1007/s12650-024-01001-0.
    2. Y. Wang, Y. Jiang, Z. Hu, C. Ruhdorfer, M. Bâce, and A. Bulling, “VisRecall++: Analysing and Predicting Visualisation Recallability from Gaze Behaviour,” Proc. ACM on Human-Computer Interaction (PACM HCI), vol. 8, pp. 1–18, Jul. 2024, doi: 10.1145/3655613.
    3. S. A. Vriend, S. Vidyapu, K.-T. Chen, and D. Weiskopf, “Which Experimental Design is Better Suited for VQA Tasks? Eye Tracking Study on Cognitive Load, Performance, and Gaze Allocations,” in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS), in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS). Jun. 2024. [Online]. Available: https://arxiv.org/abs/2404.04036
    4. D. Saupe and S. Hviid del Pin, “National differences in image quality assessment: An investigation on three large-scale IQA datasets,” in 2024 16th International Conference on Quality of Multimedia Experience (QoMEX), IEEE, Ed., in 2024 16th International Conference on Quality of Multimedia Experience (QoMEX). IEEE, May 2024, pp. 214–220. doi: 10.1109/qomex61742.2024.10598250.
    5. M. Jenadeleh, R. Hamzaoui, U.-D. Reips, and D. Saupe, “Crowdsourced Estimation of Collective Just Noticeable Difference for Compressed Video with the Flicker Test and QUEST+,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 1–1, May 2024, doi: 10.1109/tcsvt.2024.3402363.
    6. M. Jenadeleh, A. Heß, S. Hviid del Pin, E. Gamboa, M. Hirth, and D. Saupe, “Impact of feedback on crowdsourced visual quality assessment with paired comparisons,” in 2024 16th International Conference on Quality of Multimedia Experience (QoMEX), IEEE, Ed., in 2024 16th International Conference on Quality of Multimedia Experience (QoMEX). IEEE, May 2024, pp. 125–131. doi: 10.1109/qomex61742.2024.10598256.
    7. Y. Wang et al., “SalChartQA: Question-driven Saliency on Information Visualisations,” in Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI), in Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI). ACM, May 2024, pp. 1–14. doi: 10.1145/3613904.3642942.
    8. M. Kurzweg, Y. Weiss, M. O. Ernst, A. Schmidt, and K. Wolf, “Survey on Haptic Feedback through Sensory Illusions in Interactive Systems,” ACM Comput. Surv., vol. 56, no. 8, Art. no. 8, Apr. 2024, doi: 10.1145/3648353.
    9. Y. Xue et al., “Reducing Ambiguities in Line-Based Density Plots by Image-Space Colorization,” IEEE Transactions on Visualization & Computer Graphics, vol. 30, no. 1, Art. no. 1, Jan. 2024, [Online]. Available: https://www.computer.org/csdl/journal/tg/2024/01/10297597/1RyY1MBMcIo
    10. D. Weiskopf, “Bridging Quantitative and Qualitative Methods for Visualization Research: A Data/Semantics Perspective in Light of Advanced AI,” in 2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), IEEE, Ed., in 2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV). IEEE, 2024, pp. 119–128. doi: 10.1109/beliv64461.2024.00019.
    11. C. Müller and T. Ertl, “Quantifying Performance Gains of DirectStorage for the Visualisation of Time-Dependent Particle Data Sets,” Journal of Visualization, 2024, doi: 10.1007/s12650-024-01036-3.
    12. M. Jenadeleh et al., “An Image Quality Dataset with Triplet Comparisons for Multi-dimensional Scaling,” 2024, IEEE. doi: 10.1109/qomex61742.2024.10598258.
    13. S. Su et al., “Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model,” IEEE Transactions on Multimedia, vol. 26, pp. 2671–2685, 2024, doi: 10.1109/tmm.2023.3301276.
    14. D. Klötzl, T. Krake, M. Becher, M. Koch, D. Weiskopf, and K. Kurzhals, “NMF-Based Analysis of Mobile Eye-Tracking Data,” in Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, in Proceedings of the 2024 Symposium on Eye Tracking Research and Applications. 2024, pp. 1–9. doi: 10.1145/3649902.3653518.
    15. T. Krake, D. Klötzl, D. Hägele, and D. Weiskopf, “Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–16, 2024, doi: 10.1109/tvcg.2024.3364388.
    16. L. Xiao et al., “A Systematic Review of Ability-diverse Collaboration through Ability-based Lens in HCI,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, in Proceedings of the CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2024, pp. 1–21. doi: 10.1145/3613904.3641930.
    17. P. Paetzold, D. Hägele, M. Evers, D. Weiskopf, and O. Deussen, “UADAPy: An Uncertainty-Aware Visualization and Analysis Toolbox,” 2024, IEEE. doi: 10.1109/uncertaintyvisualization63963.2024.00011.
    18. M. M. Hamza, E. Ullah, A. Baggag, H. Bensmail, M. Sedlmair, and M. Aupetit, “ClustML: A measure of cluster pattern complexity in scatterplots learnt from human-labeled groupings,” Information Visualization, vol. 23, no. 2, Art. no. 2, 2024, doi: 10.1177/14738716231220536.
    19. P. Eades et al., “CelticGraph: Drawing Graphs as Celtic Knots and Links,” in Graph Drawing and Network Visualization, M. A. Bekos and M. Chimani, Eds., in Graph Drawing and Network Visualization. Cham: Springer Nature Switzerland, 2024, pp. 18–35. doi: 10.1007/978-3-031-49272-3_2.
    20. M. Becher, C. Müller, D. Sellenthin, T. Ertl, G. Reina, and D. Weiskopf, “Your Visualisations are Going Places: SciVis on Gaming Consoles,” in Proc. JapanVis, in Proc. JapanVis. 2024.
    21. F. Huth, M. Koch, M. Awad-Mohammed, K. Kurzhals, and D. Weiskopf, “Eye Tracking on Text Reading with Visual Enhancements,” in Symposium on Eye Tracking Research and Applications, in Symposium on Eye Tracking Research and Applications. New York, NY, USA: Association for Computing Machinery, 2024, p. 7. doi: 10.1145/3649902.3653521.
    22. K. Angerbauer et al., “Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR,” in The 26th International ACM SIGACCESS Conference on Computers and Accessibility, in The 26th International ACM SIGACCESS Conference on Computers and Accessibility, vol. 64. New York, NY, USA: ACM, 2024, pp. 1–15. doi: 10.1145/3663548.3675601.
    23. M. Koch, N. Pathmanathan, D. Weiskopf, and K. Kurzhals, “How Deep Is Your Gaze? Leveraging Distance in Image-Based Gaze Analysis,” in Proceedings of the 2024 Symposium on Eye Tracking Research and Applications (ETRA ’24), in Proceedings of the 2024 Symposium on Eye Tracking Research and Applications (ETRA ’24). New York, NY, USA: ACM, 2024, pp. 1–7. doi: 10.1145/3649902.3653349.
    24. L. Joos et al., “Evaluating Node Selection Techniques for Network Visualizations in Virtual Reality,” in ACM Symposium on Spatial User Interaction, in ACM Symposium on Spatial User Interaction. New York, NY, USA: ACM, 2024, pp. 1–11. doi: 10.1145/3677386.3682102.
    25. Y. Zhang, H. Williams, F. Schreiber, and K. Klein, “Visualising the Invisible : Exploring Approaches for Visual Analysis of Dynamic Airflow in Geographic Environments Using Sensor Data,” in Proceedings of the EuroVis Workshop on Visual Analytics 2024, in Proceedings of the EuroVis Workshop on Visual Analytics 2024. Eindhoven, 2024. doi: 10.2312/eurova.20241117.
    26. V. Mikheev, R. Skukies, and B. Ehinger, “The Art of Brainwaves: A Survey on Event-Related Potential Visualization Practices,” Aperture Neuro, vol. 4, 2024, doi: 10.52294/001c.116386.
    27. L. Joos, B. Jäckl, D. A. Keim, M. T. Fischer, L. Peska, and J. Lokoč, “Known-Item Search in Video: An Eye Tracking-Based Study,” in Proceedings of the 2024 International Conference on Multimedia Retrieval (ICMR ’24), in Proceedings of the 2024 International Conference on Multimedia Retrieval (ICMR ’24). New York, NY, USA: ACM, 2024, pp. 311–319. doi: 10.1145/3652583.3658119.
    28. Y. Wang, Q. Dai, M. Bâce, K. Klein, and A. Bulling, “Saliency3D: a 3D Saliency Dataset Collected on Screen,” in Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), in Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA). ACM, 2024, pp. 1–6. doi: 10.1145/3649902.3653350.
  3. 2023

    1. F. Heyen, Q. Q. Ngo, and M. Sedlmair, “Visual Overviews for Sheet Music Structure,” in Proceedings of the 24th International Society for Music Information Retrieval Conference (ISMIR) 2023, in Proceedings of the 24th International Society for Music Information Retrieval Conference (ISMIR) 2023. ISMIR, Dec. 2023, pp. 692–699. doi: 10.5281/zenodo.10265383.
    2. C. Beck and M. Köllner, “GHisBERT – Training BERT from scratch for lexical semantic investigations across historical German language stages,” in Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change, N. Tahmasebi, S. Montariol, H. Dubossarsky, A. Kutuzov, S. Hengchen, D. Alfter, F. Periti, and P. Cassotti, Eds., in Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change. Singapore: Association for Computational Linguistics, Dec. 2023, pp. 33–45. [Online]. Available: https://aclanthology.org/2023.lchange-1.4
    3. J. Zagermann, S. Hubenschmid, D. I. Fink, J. Wieland, H. Reiterer, and T. Feuchtner, “Challenges and Opportunities for Collaborative Immersive Analytics with Hybrid User Interfaces,” in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). Los Alamitos, CA, USA: IEEE Computer Society, Oct. 2023, pp. 191–195. doi: 10.1109/ISMAR-Adjunct60411.2023.00044.
    4. J. Schmalfuß, L. Mehl, and A. Bruhn, “Distracting Downpour: Adversarial Weather Attacks for Motion Estimation,” in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). Oct. 2023, pp. 10106–10116. [Online]. Available: https://openaccess.thecvf.com/content/ICCV2023/html/Schmalfuss_Distracting_Downpour_Adversarial_Weather_Attacks_for_Motion_Estimation_ICCV_2023_paper.html
    5. L. Hirsch, F. Müller, F. Chiossi, T. Benga, and A. M. Butz, “My Heart Will Go On: Implicitly Increasing Social Connectedness by Visualizing Asynchronous Players’ Heartbeats in VR Games,” Proc. ACM Hum.-Comput. Interact., vol. 7, Oct. 2023, doi: 10.1145/3611057.
    6. O. Wiedemann, V. Hosu, S. Su, and D. Saupe, “Konx: cross-resolution image quality assessment,” Quality and User Experience, vol. 8, no. 1, Art. no. 1, Aug. 2023, doi: 10.1007/s41233-023-00061-8.
    7. E. Sood, L. Shi, M. Bortoletto, Y. Wang, P. Müller, and A. Bulling, “Improving Neural Saliency Prediction with a Cognitive Model of Human Visual Attention,” in Proceedings of the 45th Annual Meeting of the Cognitive Science Society (CogSci), in Proceedings of the 45th Annual Meeting of the Cognitive Science Society (CogSci). Jul. 2023, pp. 3639–3646. [Online]. Available: https://escholarship.org/uc/item/5968p71m
    8. G. Chen, H. Lin, O. Wiedemann, and D. Saupe, “Localization of Just Noticeable Difference for Image Compression,” in 2023 15th International Conference on Quality of Multimedia Experience (QoMEX), in 2023 15th International Conference on Quality of Multimedia Experience (QoMEX). Jun. 2023, pp. 61–66. doi: 10.1109/QoMEX58391.2023.10178653.
    9. L. Mehl, J. Schmalfuß, A. Jahedi, Y. Nalivayko, and A. Bruhn, “Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Jun. 2023, pp. 4981–4991. [Online]. Available: https://openaccess.thecvf.com/content/CVPR2023/html/Mehl_Spring_A_High-Resolution_High-Detail_Dataset_and_Benchmark_for_Scene_Flow_CVPR_2023_paper.html
    10. X. Zhao et al., “CUDAS: Distortion-Aware Saliency Benchmark,” IEEE Access, vol. 11, pp. 58025–58036, Jun. 2023, doi: 10.1109/access.2023.3283344.
    11. K.-T. Chen et al., “Gazealytics : A Unified and Flexible Visual Toolkit for Exploratory and Comparative Gaze Analysis,” in ETRA ’23 : Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, in ETRA ’23 : Proceedings of the 2023 Symposium on Eye Tracking Research and Applications. Association for Computing Machinery, May 2023, pp. 1–7. doi: 10.1145/3588015.3589844.
    12. M. Kern, S. Jaeger-Honz, F. Schreiber, and B. Sommer, “APL@voro—interactive visualization and analysis of cell membrane simulations,” Bioinformatics, vol. 39, no. 2, Art. no. 2, Feb. 2023, doi: 10.1093/bioinformatics/btad083.
    13. Y. Wang, M. Bâce, and A. Bulling, “Scanpath Prediction on Information Visualisations,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–15, Feb. 2023, doi: 10.1109/TVCG.2023.3242293.
    14. L. Mehl, A. Jahedi, J. Schmalfuß, and A. Bruhn, “M-FUSE: Multi-frame Fusion for Scene Flow Estimation,” in Proc. Winter Conference on Applications of Computer Vision (WACV), in Proc. Winter Conference on Applications of Computer Vision (WACV). Jan. 2023. doi: 10.48550/arXiv.2207.05704.
    15. T. Kosch, J. Karolus, J. Zagermann, H. Reiterer, A. Schmidt, and P. W. Woźniak, “A Survey on Measuring Cognitive Workload in Human-Computer Interaction,” ACM Comput. Surv., Jan. 2023, doi: 10.1145/3582272.
    16. N. Rodrigues, C. Schulz, S. Döring, D. Baumgartner, T. Krake, and D. Weiskopf, “Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, Art. no. 1, Jan. 2023, doi: 10.1109/TVCG.2022.3209429.
    17. M. Koch, K. Kurzhals, M. Burch, and D. Weiskopf, “Visualization Psychology for Eye Tracking Evaluation,” in Visualization Psychology, D. Albers Szafir, R. Borgo, M. Chen, D. J. Edwards, B. Fisher, and L. Padilla, Eds., in Visualization Psychology. , Cham: Springer International Publishing, 2023, pp. 243–260. doi: 10.1007/978-3-031-34738-2_10.
    18. N. Doerr, K. Angerbauer, M. Reinelt, and M. Sedlmair, “Bees, Birds and Butterflies: Investigating the Influence of Distractors on Visual Attention Guidance Techniques,” in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, in Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery, 2023. doi: 10.1145/3544549.3585816.
    19. E. Pangratz, F. Chiossi, S. Villa, K. Gramann, and L. Gehrke, “Towards an Implicit Metric of Sensory-Motor Accuracy: Brain Responses to Auditory Prediction Errors in Pianists,” in Proceedings of the 15th Conference on Creativity and Cognition, in Proceedings of the 15th Conference on Creativity and Cognition. New York, NY, USA: Association for Computing Machinery, 2023, pp. 129–138. doi: 10.1145/3591196.3593340.
    20. A. Zaky, J. Zagermann, H. Reiterer, and T. Feuchtner, “Opportunities and Challenges of Hybrid User Interfaces for Optimization of Mixed Reality Interfaces,” in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 2023, pp. 215–219. [Online]. Available: https://ieeexplore.ieee.org/document/10322176
    21. J. Wieland, “Designing and Evaluating Interactions for Handheld AR,” in Companion Proceedings of the 2023 Conference on Interactive Surfaces and Spaces, in Companion Proceedings of the 2023 Conference on Interactive Surfaces and Spaces. New York, NY, USA: Association for Computing Machinery, 2023, pp. 100–103. doi: 10.1145/3626485.3626555.
    22. A. V. Reinschluessel and J. Zagermann, “Exploring Hybrid User Interfaces for Surgery Planning,” in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 2023, pp. 208–210. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/10322244
    23. M. Testolina, V. Hosu, M. Jenadeleh, D. Lazzarotto, D. Saupe, and T. Ebrahimi, “JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range,” in 15th International Conference on Quality of Multimedia Experience (QoMEX), in 15th International Conference on Quality of Multimedia Experience (QoMEX). 2023, pp. 55–60. [Online]. Available: https://ieeexplore.ieee.org/document/10178554
    24. R. Bauer et al., “Visual Ensemble Analysis of Fluid Flow in Porous Media across Simulation Codes and Experiment,” Transport in Porous Media, 2023, doi: 10.1007/s11242-023-02019-y#citeas.
    25. C. Morariu, A. Bibal, R. Cutura, B. Frénay, and M. Sedlmair, “Predicting User Preferences of Dimensionality Reduction Embedding Quality,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, Art. no. 1, 2023, [Online]. Available: https://ieeexplore.ieee.org/document/9904619
    26. T. Ge et al., “Optimally Ordered Orthogonal Neighbor Joining Trees for Hierarchical Cluster Analysis,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–13, 2023, [Online]. Available: https://ieeexplore.ieee.org/document/10147241
    27. W. Kerle-Malcharek, S. P. Feyer, F. Schreiber, and K. Klein, “GAV-VR: An Extensible Framework for Graph Analysis and Visualisation in Virtual Reality,” in ICAT-EGVE 2023 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, J.-M. Normand, M. Sugimoto, and V. Sundstedt, Eds., in ICAT-EGVE 2023 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments. The Eurographics Association, 2023. doi: 10.2312/egve.20231321.
    28. M. Xue et al., “Taurus: Towards a Unified Force Representation and Universal Solver for Graph Layout,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, Art. no. 1, 2023, doi: 10.1109/TVCG.2022.3209371.
    29. M. Butt, L. Carnesale, and T. Ahmed, “Experiencers vs. agents in Urdu/Hindi nominalized verbs of perception,” in Proceedings of the Lexical Functional Grammar Conference, in Proceedings of the Lexical Functional Grammar Conference, vol. 28. 2023, pp. 90–113. [Online]. Available: https://lfg-proceedings.org/lfg/index.php/main/article/view/46
    30. K.-T. Chen et al., “Reading Strategies for Graph Visualizations That Wrap Around in Torus Topology,” in Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, in Proceedings of the 2023 Symposium on Eye Tracking Research and Applications. New York, NY, USA: Association for Computing Machinery, 2023. doi: 10.1145/3588015.3589841.
    31. A. Jahedi, M. Luz, M. Rivinius, L. Mehl, and A. Bruhn, “MS-RAFT+: High Resolution Multi-Scale RAFT,” International Journal of Computer Vision, pp. 1573–1405, 2023, doi: 10.1007/s11263-023-01930-7.
    32. F. Draxler, A. Schmidt, and L. L. Chuang, “Relevance, Effort, and Perceived Quality: Language Learners’ Experiences with AI-Generated Contextually Personalized Learning Material,” in Proceedings of the 2023 ACM Designing Interactive Systems Conference, in Proceedings of the 2023 ACM Designing Interactive Systems Conference. New York, NY, USA: Association for Computing Machinery, 2023, pp. 2249–2262. doi: 10.1145/3563657.3596112.
    33. W. Teramoto and M. O. Ernst, “Effects of invisible lip movements on phonetic perception,” Scientific Reports, vol. 13, no. 1, Art. no. 1, 2023, doi: 10.1038/s41598-023-33791-y.
    34. S. Hubenschmid, D. I. Fink, J. Zagermann, J. Wieland, H. Reiterer, and T. Feuchtner, “Colibri: A Toolkit for Rapid Prototyping of Networking Across Realities,” in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), in 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 2023, pp. 9–13. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/10322249
    35. M. Jenadeleh, J. Zagermann, H. Reiterer, U.-D. Reips, R. Hamzaoui, and D. Saupe, “Relaxed forced choice improves performance of visual quality assessment methods,” in 2023 15th International Conference on Quality of Multimedia Experience (QoMEX), in 2023 15th International Conference on Quality of Multimedia Experience (QoMEX). 2023, pp. 37–42. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/10178467
    36. C. Schneegass, M. L. Wilson, H. A. Maior, F. Chiossi, A. L. Cox, and J. Wiese, “The Future of Cognitive Personal Informatics,” in Proceedings of the 25th International Conference on Mobile Human-Computer Interaction, in Proceedings of the 25th International Conference on Mobile Human-Computer Interaction. New York, NY, USA: Association for Computing Machinery, 2023. doi: 10.1145/3565066.3609790.
    37. P. Paetzold, R. Kehlbeck, H. Strobelt, Y. Xue, S. Storandt, and O. Deussen, “RectEuler: Visualizing Intersecting Sets using Rectangles,” Computer Graphics Forum, vol. 42, no. 3, Art. no. 3, 2023, doi: 10.1111/cgf.14814.
    38. F. L. Dennig, M. Miller, D. A. Keim, and M. El-Assady, “FS/DS: A Theoretical Framework for the Dual Analysis of Feature Space and Data Space,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–17, 2023, [Online]. Available: https://ieeexplore.ieee.org/document/10158903
    39. J. Schmalfuß, E. Scheurer, H. Zhao, N. Karantzas, A. Bruhn, and D. Labate, “Blind image inpainting with sparse directional filter dictionaries for lightweight CNNs,” Journal of Mathematical Imaging and Vision (JMIV), vol. 65, pp. 323–339, 2023, doi: 10.1007/s10851-022-01119-6.
    40. M. Gleicher, M. Riveiro, T. von Landesberger, O. Deussen, R. Chang, and C. Gillman, “A Problem Space for Designing Visualizations,” IEEE Computer Graphics and Applications, vol. 43, no. 4, Art. no. 4, 2023, [Online]. Available: https://ieeexplore.ieee.org/document/10179119
    41. S. Hubenschmid, J. Zagermann, D. Leicht, H. Reiterer, and T. Feuchtner, “ARound the Smartphone: Investigating the Effects of Virtually-Extended Display Size on Spatial Memory,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23). New York, NY, USA: ACM, 2023. [Online]. Available: https://kops.uni-konstanz.de/server/api/core/bitstreams/6eecac2f-666f-4399-bec3-d8e607331164/content
  4. 2022

    1. D. I. Fink, J. Zagermann, H. Reiterer, and H.-C. Jetter, “Re-Locations: Augmenting Personal and Shared Workspaces to Support Remote Collaboration in Incongruent Spaces,” Proc. ACM Hum.-Comput. Interact., vol. 6, Nov. 2022, doi: 10.1145/3567709.
    2. A. Jahedi, L. Mehl, M. Rivinius, and A. Bruhn, “Multi-Scale RAFT: combining hierarchical concepts for learning-based optical flow estimation,” in Proceedings of the IEEE International Conference on Image Processing (ICIP), in Proceedings of the IEEE International Conference on Image Processing (ICIP). Oct. 2022, pp. 1236–1240. doi: 10.48550/arXiv.2207.12163.
    3. K. Angerbauer and M. Sedlmair, “Toward Inclusion and Accessibility in Visualization Research: Speculations on Challenges, Solution Strategies, and Calls for Action (Position Paper),” in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), in 2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV). Oct. 2022, pp. 20–27. [Online]. Available: https://ieeexplore.ieee.org/document/9978448
    4. C. Müller, M. Heinemann, D. Weiskopf, and T. Ertl, “Power Overwhelming: Quantifying the Energy Cost of Visualisation,” in Proceedings of the 2022 IEEE Workshop on Evaluation and Beyond - Methodological Approaches for Visualization (BELIV), in Proceedings of the 2022 IEEE Workshop on Evaluation and Beyond - Methodological Approaches for Visualization (BELIV). Oct. 2022, pp. 38–46. doi: 10.1109/BELIV57783.2022.00009.
    5. J. Schmalfuß, P. Scholze, and A. Bruhn, “A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow,” Proceedings of the European Conference on Computer Vision (ECCV), Oct. 2022, doi: 10.1007/978-3-031-20047-2_11.
    6. H. Lin, H. Men, Y. Yan, J. Ren, and D. Saupe, “Crowdsourced Quality Assessment of Enhanced Underwater Images - a Pilot Study,” in Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX), in Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX). IEEE, Sep. 2022, pp. 1–4. [Online]. Available: https://ieeexplore.ieee.org/document/9900904
    7. S. Dosdall, K. Angerbauer, L. Merino, M. Sedlmair, and D. Weiskopf, “Toward In-Situ Authoring of Situated Visualization with Chorded Keyboards,” in 15th International Symposium on Visual Information Communication and Interaction, VINCI 2022, Chur, Switzerland, August 16-18, 2022, M. Burch, G. Wallner, and D. Limberger, Eds., in 15th International Symposium on Visual Information Communication and Interaction, VINCI 2022, Chur, Switzerland, August 16-18, 2022. ACM, Aug. 2022, pp. 1–5. doi: 10.1145/3554944.3554970.
    8. P. Schäfer, N. Rodrigues, D. Weiskopf, and S. Storandt, “Group Diagrams for Simplified Representation of Scanpaths,” in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI), in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI). ACM, Aug. 2022. doi: 10.1145/3554944.3554971.
    9. M. Zameshina et al., “Fairness in generative modeling: do it unsupervised!,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, in Proceedings of the Genetic and Evolutionary Computation Conference Companion. ACM, Jul. 2022, pp. 320–323. doi: 10.1145/3520304.3528992.
    10. Y. Wang, M. Koch, M. Bâce, D. Weiskopf, and A. Bulling, “Impact of Gaze Uncertainty on AOIs in Information Visualisations,” in 2022 Symposium on Eye Tracking Research and Applications, in 2022 Symposium on Eye Tracking Research and Applications. ACM, Jun. 2022, pp. 1–6. doi: 10.1145/3517031.3531166.
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    12. M. Koch, D. Weiskopf, and K. Kurzhals, “A Spiral into the Mind: Gaze Spiral Visualization for Mobile Eye Tracking,” Proceedings of the ACM on Computer Graphics and Interactive Techniques, vol. 5, no. 2, Art. no. 2, May 2022, doi: 10.1145/3530795.
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    24. T. Krake, M. von Scheven, J. Gade, M. Abdelaal, D. Weiskopf, and M. Bischoff, “Efficient Update of Redundancy Matrices for Truss and Frame Structures,” Journal of Theoretical, Computational and Applied Mechanics, 2022, [Online]. Available: https://jtcam.episciences.org/10398
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    37. Y. Zhang, K. Klein, O. Deussen, T. Gutschlag, and S. Storandt, “Robust Visualization of Trajectory Data,” it - Information Technology, vol. 64, pp. 181–191, 2022, doi: 10.1515/itit-2022-0036.
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    40. M. Abdelaal, N. D. Schiele, K. Angerbauer, K. Kurzhals, M. Sedlmair, and D. Weiskopf, “Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations,” IEEE Transactions on Visualization and Computer Graphics, pp. 1–11, 2022.
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    44. M. Abdelaal, N. D. Schiele, K. Angerbauer, K. Kurzhals, M. Sedlmair, and D. Weiskopf, “Supplemental Materials for: Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations,” 2022, DaRUS. [Online]. Available: https://darus.uni-stuttgart.de/citation?persistentId=doi:10.18419/darus-3100
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  5. 2021

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    7. P. Balestrucci, V. Maffei, F. Lacquaniti, and A. Moscatelli, “The Effects of Visual Parabolic Motion on the Subjective Vertical and on Interception,” Neuroscience, vol. 453, pp. 124–137, Jan. 2021, [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0306452220306424
    8. T. Krake, S. Reinhardt, M. Hlawatsch, B. Eberhardt, and D. Weiskopf, “Visualization and Selection of Dynamic Mode Decomposition Components for Unsteady Flow,” Visual Informatics, vol. 5, no. 3, Art. no. 3, 2021, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2468502X21000309
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    13. F. Götz-Hahn, V. Hosu, H. Lin, and D. Saupe, “KonVid-150k : A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild,” IEEE Access, vol. 9, pp. 72139–72160, 2021, doi: 10.1109/ACCESS.2021.3077642.
    14. J. Bernard, M. Hutter, M. Zeppelzauer, M. Sedlmair, and T. Munzner, “ProSeCo: Visual analysis of class separation measures and dataset characteristics,” Computers & Graphics, vol. 96, pp. 48–60, 2021, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0097849321000406
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    16. M. M. Abbas, E. Ullah, A. Baggag, H. Bensmail, M. Sedlmair, and M. Aupetit, “ClustRank: A Visual Quality Measure Trained on Perceptual Data for Sorting Scatterplots by Cluster Patterns,” 2021. [Online]. Available: https://arxiv.org/pdf/2106.00599.pdf
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    18. S. Giebenhain and B. Goldlücke, “AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit Representations,” in 2021 International Conference on 3D Vision (3DV), in 2021 International Conference on 3D Vision (3DV). 2021, pp. 1054–1064. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9665836
    19. M. Kraus et al., “Immersive Analytics with Abstract 3D Visualizations: A Survey,” Computer Graphics Forum, 2021, doi: 10.1111/cgf.14430.
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    21. H. Lin, G. Chen, and F. W. Siebert, “Positional Encoding: Improving Class-Imbalanced Motorcycle Helmet use Classification,” in 2021 IEEE International Conference on Image Processing (ICIP), in 2021 IEEE International Conference on Image Processing (ICIP). 2021, pp. 1194–1198. [Online]. Available: https://ieeexplore.ieee.org/document/9506178
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    23. K. Vock, S. Hubenschmid, J. Zagermann, S. Butscher, and H. Reiterer, “IDIAR : Augmented Reality Dashboards to Supervise Mobile Intervention Studies,” in Mensch und Computer 2021 (MuC ’21), in Mensch und Computer 2021 (MuC ’21). New York, NY: ACM, 2021. [Online]. Available: http://nbn-resolving.de/urn:nbn:de:bsz:352-2-22ydtfzvxx3l1
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    27. C. Krauter, J. Vogelsang, A. Sousa Calepso, K. Angerbauer, and M. Sedlmair, “Don’t Catch It: An Interactive Virtual-Reality Environment to Learn About COVID-19 Measures Using Gamification Elements,” in Mensch und Computer, in Mensch und Computer. ACM, 2021, pp. 593–596. doi: 10.1145/3473856.3474031.
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    29. S. Hubenschmid, J. Zagermann, D. I. Fink, J. Wieland, T. Feuchtner, and H. Reiterer, “Towards Asynchronous Hybrid User Interfaces for Cross-Reality Interaction,” in ISS’21 Workshop Proceedings: “Transitional Interfaces in Mixed and Cross-Reality: A new frontier?,” H.-C. Jetter, J.-H. Schröder, J. Gugenheimer, M. Billinghurst, C. Anthes, M. Khamis, and T. Feuchtner, Eds., in ISS’21 Workshop Proceedings: “Transitional Interfaces in Mixed and Cross-Reality: A new frontier?” 2021. [Online]. Available: https://kops.uni-konstanz.de/bitstream/handle/123456789/55453/Hubenschmid_2-84mm0sggczq02.pdf?sequence=1&isAllowed=y
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  6. 2020

    1. C. Beck, “DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT Embeddings,” in Proceedings of the Fourteenth Workshop on Semantic Evaluation, in Proceedings of the Fourteenth Workshop on Semantic Evaluation. Barcelona (online): International Committee for Computational Linguistics, Dec. 2020, pp. 50–58. [Online]. Available: https://www.aclweb.org/anthology/2020.semeval-1.4
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  7. 2019

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    4. H. Zhang, S. Frey, H. Steeb, D. Uribe, T. Ertl, and W. Wang, “Visualization of Bubble Formation in Porous Media,” IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 1, Art. no. 1, 2019, [Online]. Available: https://ieeexplore.ieee.org/document/8445644
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    21. C. Schätzle, F. L. Dennig, M. Blumenschein, D. A. Keim, and M. Butt, “Visualizing Linguistic Change as Dimension Interactions,” in Proceedings of the International Workshop on Computational Approaches to Historical Language Change, in Proceedings of the International Workshop on Computational Approaches to Historical Language Change. 2019, pp. 272–278. [Online]. Available: https://www.aclweb.org/anthology/W19-4734.pdf
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    23. J. Görtler, M. Spicker, C. Schulz, D. Weiskopf, and O. Deussen, “Stippling of 2D Scalar Fields,” IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 6, Art. no. 6, 2019, [Online]. Available: https://ieeexplore.ieee.org/document/8667696
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  9. 2017

    1. O. Deussen, M. Spicker, and Q. Zheng, “Weighted Linde-Buzo-Gray Stippling,” ACM Transactions on Graphics, vol. 36, no. 6, Art. no. 6, Nov. 2017, doi: 10.1145/3130800.3130819.
    2. M. Stoll, D. Maurer, S. Volz, and A. Bruhn, “Illumination-aware Large Displacement Optical Flow,” in Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, M. Pelillo and E. R. Hancock, Eds., in Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, vol. 10746. Springer International Publishing, 2017, pp. 139–154. doi: 10.1007/978-3-319-78199-0_10.
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    4. D. Maurer, M. Stoll, S. Volz, P. Gairing, and A. Bruhn, “A Comparison of Isotropic and Anisotropic Second Order Regularisers for Optical Flow,” in Scale Space and Variational Methods in Computer Vision. SSVM 2017. Lecture Notes in Computer Science, vol. 10302, F. Lauze, Y. Dong, and A. B. Dahl, Eds., in Scale Space and Variational Methods in Computer Vision. SSVM 2017. Lecture Notes in Computer Science, vol. 10302. , Springer International Publishing, 2017, pp. 537–549. doi: 10.1007/978-3-319-58771-4_43.
    5. M. Herschel, R. Diestelkämper, and H. Ben Lahmar, “A Survey on Provenance - What for? What form? What from?,” The VLDB Journal, vol. 26, pp. 881–906, 2017, doi: 10.1007/s00778-017-0486-1.
    6. N. Rodrigues et al., “Visualization of Time Series Data with Spatial Context: Communicating the Energy Production of Power Plants,” in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI), in Proceedings of the ACM Symposium on Visual Information Communication and Interaction (VINCI). 2017, pp. 37–44. doi: 10.1145/3105971.3105982.
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    8. R. Netzel, J. Vuong, U. Engelke, S. I. O’Donoghue, D. Weiskopf, and J. Heinrich, “Comparative Eye-tracking Evaluation of Scatterplots and Parallel Coordinates,” Visual Informatics, vol. 1, no. 2, Art. no. 2, 2017, doi: 10.1016/j.visinf.2017.11.001.
    9. M. Stoll, D. Maurer, and A. Bruhn, “Variational Large Displacement Optical Flow without Feature Matches,” in Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science, E. R. Hancock and M. Pelillo, Eds., in Proceedings of International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR). Lecture Notes in Computer Science. Springer, 2017.
    10. H. V. Le, V. Schwind, P. Göttlich, and N. Henze, “PredicTouch: A System to Reduce Touchscreen Latency using Neural Networks and Inertial Measurement Units,” in Proceedings of the ACM International Conference on Interactive Surfaces and Spaces (ISS), ACM, Ed., in Proceedings of the ACM International Conference on Interactive Surfaces and Spaces (ISS), vol. 17. ACM, 2017, pp. 230–239. doi: 10.1145/3132272.3134138.
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    72. H. Booth, C. Schätzle, K. Börjars, and M. Butt, “Dative Subjects and the Rise of Positional Licensing in Icelandic,” in Proceedings of the LFG’17 Conference, in Proceedings of the LFG’17 Conference. 2017, pp. 104–124. [Online]. Available: http://web.stanford.edu/group/cslipublications/cslipublications/LFG/LFG-2017/lfg2017-bsbb.pdf
    73. X. Zhang, Y. Sugano, and A. Bulling, “Everyday Eye Contact Detection Using Unsupervised Gaze Target Discovery,” in Proceedings of the ACM Symposium on User Interface Software and Technology (UIST), in Proceedings of the ACM Symposium on User Interface Software and Technology (UIST). 2017, pp. 193–203. doi: 10.1145/3126594.3126614.
    74. M. Spicker, F. Hahn, T. Lindemeier, D. Saupe, and O. Deussen, “Quantifying Visual Abstraction Quality for Stipple Drawings,” in Proceedings of the Symposium on Non-Photorealistic Animation and Rendering (NPAR), ACM, Ed., in Proceedings of the Symposium on Non-Photorealistic Animation and Rendering (NPAR). Association for Computing Machinery, 2017, pp. 8:1-8:10. doi: 10.1145/3092919.3092923.
    75. M. Stein et al., “Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis,” in IEEE Transactions on Visualization and Computer Graphics, in IEEE Transactions on Visualization and Computer Graphics, vol. 24. 2017, pp. 13–22. [Online]. Available: https://ieeexplore.ieee.org/document/8019849
    76. V. Schwind, K. Wolf, and N. Henze, “FaceMaker - A Procedural Face Generator to Foster Character Design Research,” O. Korn and N. Lee, Eds., Springer International Publishing, 2017, pp. 95–113. doi: 10.1007/978-3-319-53088-8_6.
    77. K. de Winkel, A. Nesti, H. Ayaz, and H. H. Bülthoff, “Neural Correlates of Decision Making on Whole Body Yaw Rotation: an fNIRS Study,” Neuroscience Letters, vol. 654, pp. 56–62, 2017, doi: 10.1016/j.neulet.2017.04.053.
    78. V. Schwind, P. Knierim, L. L. Chuang, and N. Henze, “‘Where’s Pinky?’: The Effects of a Reduced Number of Fingers in Virtual Reality,” in Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI PLAY), B. A. M. Schouten, P. Markopoulos, Z. O. Toups, P. A. Cairns, and T. Bekker, Eds., in Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI PLAY). ACM, 2017, pp. 507–515. doi: 10.1145/3116595.3116596.
    79. P. Tutzauer and N. Haala, “Processing of Crawled Urban Imagery for Building Use Classification,” ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 143–149, 2017, doi: 10.5194/isprs-archives-XLII-1-W1-143-2017.
  10. 2016

    1. L. Lischke, S. Mayer, K. Wolf, N. Henze, H. Reiterer, and A. Schmidt, “Screen arrangements and interaction areas for large display work places,” in PerDis ’16 Proceedings of the 5th ACM International Symposium on Pervasive Displays, ACM, Ed., in PerDis ’16 Proceedings of the 5th ACM International Symposium on Pervasive Displays, vol. 5. ACM, 2016, pp. 228–234. doi: 10.1145/2914920.2915027.
    2. A. Barth, R. Bürger, I. Kröker, and C. Rohde, “Computational Uncertainty Quantification for a Clarifier-thickener Model with Several Random Perturbations: A Hybrid Stochastic Galerkin Approach,” Computers & Chemical Engineering, vol. 89, pp. 11–26, 2016, doi: 10.1016/j.compchemeng.2016.02.016.
    3. A. Barth and F. G. Fuchs, “Uncertainty Quantification for Hyperbolic Conservation Laws with Flux Coefficients Given by Spatiotemporal Random Fields,” SIAM Journal on Scientific Computing, vol. 38, no. 4, Art. no. 4, 2016, doi: 10.1137/15M1027723.
    4. J. Zagermann, U. Pfeil, R. Rädle, H.-C. Jetter, C. N. Klokmose, and H. Reiterer, “When Tablets meet Tabletops: The Effect of Tabletop Size on Around-the-Table Collaboration with Personal Tablets,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, J. Kaye, A. Druin, C. Lampe, D. Morris, and J. P. Hourcade, Eds., in Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, 2016, pp. 5470–5481. doi: 10.1145/2858036.2858224.
    5. X. Zhang, Y. Sugano, M. Fritz, and A. Bulling, “It’s Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2016, pp. 2299–2308. [Online]. Available: https://ieeexplore.ieee.org/document/8015018
    6. N. Flad, J. C. Ditz, A. Schmidt, H. H. Bülthoff, and L. L. Chuang, “Data-Driven Approaches to Unrestricted Gaze-Tracking Benefit from Saccade Filtering,” in Proceedings of the Second Workshop on Eye Tracking and Visualization (ETVIS), M. Burch, L. L. Chuang, and A. T. Duchowski, Eds., in Proceedings of the Second Workshop on Eye Tracking and Visualization (ETVIS). IEEE, 2016, pp. 1–5. [Online]. Available: https://ieeexplore.ieee.org/document/7851156
    7. P. Tutzauer, S. Becker, D. Fritsch, T. Niese, and O. Deussen, “A Study of the Human Comprehension of Building Categories Based on Different 3D Building Representations,” Photogrammetrie - Fernerkundung - Geoinformation, vol. 2016, pp. 319–333, 2016, doi: 10.1127/pfg/2016/0302.
    8. K. Kurzhals, B. Fisher, M. Burch, and D. Weiskopf, “Eye Tracking Evaluation of Visual Analytics,” Information Visualization, vol. 15, no. 4, Art. no. 4, 2016, doi: 10.1177/1473871615609787.
    9. C. Schulz et al., “Generative Data Models for Validation and Evaluation of Visualization Techniques,” in Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV), in Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV). ACM, 2016, pp. 112–124. doi: 10.1145/2993901.2993907.
    10. D. Sacha et al., “Human-Centered Machine Learning Through Interactive Visualization: Review and Open Challenges.,” in Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), in Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN). 2016. [Online]. Available: http://dblp.uni-trier.de/db/conf/esann/esann2016.html#SachaSZLWNK16
    11. D. Weiskopf, M. Burch, L. L. Chuang, B. Fischer, and A. Schmidt, Eye Tracking and Visualization: Foundations, Techniques, and Applications. Berlin, Heidelberg: Springer, 2016. [Online]. Available: https://www.springer.com/de/book/9783319470238
    12. K. Kurzhals, M. Hlawatsch, M. Burch, and D. Weiskopf, “Fixation-Image Charts,” in Proceedings of the Symposium on Eye Tracking Research & Applications (ETRA), ACM, Ed., in Proceedings of the Symposium on Eye Tracking Research & Applications (ETRA), vol. 1. ACM, 2016, pp. 11–18. doi: 10.1145/2857491.2857507.
    13. A. Nocaj, M. Ortmann, and U. Brandes, “Adaptive Disentanglement Based on Local Clustering in Small-World Network Visualization,” IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 6, Art. no. 6, 2016, [Online]. Available: http://dblp.uni-trier.de/db/journals/tvcg/tvcg22.html#NocajOB16
    14. B. Pfleging, D. K. Fekety, A. Schmidt, and A. L. Kun, “A Model Relating Pupil Diameter to Mental Workload and Lighting Conditions,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, J. Kaye, A. Druin, C. Lampe, D. Morris, and J. P. Hourcade, Eds., in Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, 2016, pp. 5776–5788. doi: 10.1145/2858036.2858117.
    15. J. Müller, R. Rädle, and H. Reiterer, “Virtual Objects as Spatial Cues in Collaborative Mixed Reality Environments: How They Shape Communication Behavior and User Task Load,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, J. Kaye, A. Druin, C. Lampe, D. Morris, and J. P. Hourcade, Eds., in Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, 2016, pp. 1245–1249. doi: 10.1145/2858036.2858043.
    16. P. Xu, Y. Sugano, and A. Bulling, “Spatio-Temporal Modeling and Prediction of Visual Attention in Graphical User Interfaces,” in Proceedings of the CHI Conference on Human Factors in Computing Systems, in Proceedings of the CHI Conference on Human Factors in Computing Systems. 2016, pp. 3299–3310.
    17. E. Wood, T. Baltrusaitis, L.-P. Morency, P. Robinson, and A. Bulling, “Learning an Appearance-Based Gaze Estimator from One Million Synthesised Images,” in Proceedings of the Symposium on Eye Tracking Research & Applications (ETRA), in Proceedings of the Symposium on Eye Tracking Research & Applications (ETRA). 2016, pp. 131–138. doi: 10.1145/2857491.2857492.
    18. V. Hosu, F. Hahn, O. Wiedemann, S.-H. Jung, and D. Saupe, “Saliency-driven Image Coding Improves Overall Perceived JPEG Quality,” in Proceedings of the Picture Coding Symposium (PCS), in Proceedings of the Picture Coding Symposium (PCS). IEEE, 2016, pp. 1–5. [Online]. Available: https://www.uni-konstanz.de/mmsp/pubsys/publishedFiles/HoHaWi16.pdf
    19. M. Hund et al., “Visual Quality Assessment of Subspace Clusterings,” in Proceedings of the KDD Workshop on Interactive Data Exploration and Analytics (IDEA), I. KDD 2016, Ed., in Proceedings of the KDD Workshop on Interactive Data Exploration and Analytics (IDEA). 2016, pp. 53–62.
    20. S. Frey and T. Ertl, “Auto-Tuning Intermediate Representations for In Situ Visualization,” in Proceedings of the New York Scientific Data Summit (NYSDS), in Proceedings of the New York Scientific Data Summit (NYSDS). IEEE, 2016, pp. 1–10. [Online]. Available: https://ieeexplore.ieee.org/document/7747807
    21. M. Hund et al., “Visual Analytics for Concept Exploration in Subspaces of Patient Groups,” Brain Informatics, vol. 3, no. 4, Art. no. 4, 2016, doi: 10.1007/s40708-016-0043-5.
    22. M. Aupetit and M. Sedlmair, “SepMe: 2002 New Visual Separation Measures.,” in Proceedings of the IEEE Pacific Visualization Symposium (PacificVis), C. Hansen, I. Viola, and X. Yuan, Eds., in Proceedings of the IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2016, pp. 1–8. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7465244
    23. L. Lischke, V. Schwind, K. Friedrich, A. Schmidt, and N. Henze, “MAGIC-Pointing on Large High-Resolution Displays,” in Proceedings of the CHI Conference on Human Factors in Computing Systems-Extended Abstracts (CHI-EA), ACM, Ed., in Proceedings of the CHI Conference on Human Factors in Computing Systems-Extended Abstracts (CHI-EA). ACM, 2016, pp. 1706–1712. doi: 10.1145/2851581.2892479.
    24. P. Tutzauer, S. Becker, T. Niese, O. Deussen, and D. Fritsch, “Understanding Human Perception of Building Categories in Virtual 3d Cities - a User Study,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS), pp. 683–687, 2016, [Online]. Available: https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/683/2016/isprs-archives-XLI-B2-683-2016.pdf
    25. S. Cheng and K. Mueller, “The Data Context Map: Fusing Data and Attributes into a Unified Display.,” IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 1, Art. no. 1, 2016, [Online]. Available: http://dblp.uni-trier.de/db/journals/tvcg/tvcg22.html#ChengM16
    26. T. Dingler, R. Rzayev, V. Schwind, and N. Henze, “RSVP on the go - Implicit Reading Support on Smart Watches Through Eye Tracking,” in Proceedings of the ACM International Symposium on Wearable Computers (ISWC), ACM, Ed., in Proceedings of the ACM International Symposium on Wearable Computers (ISWC). 2016, pp. 116–119. doi: 10.1145/2971763.2971794.
    27. M. Scheer, H. H. Bülthoff, and L. L. Chuang, “Steering Demands Diminish the Early-P3, Late-P3 and RON Components of the Event-Related Potential of Task-Irrelevant Environmental Sounds,” in Frontiers in Human Neuroscience, F. in Human Neuroscience, Ed., in Frontiers in Human Neuroscience, vol. 10. 2016, pp. 73:1-73:15. doi: 10.3389/fnhum.2016.00073.
    28. C. Schätzle and D. Sacha, “Visualizing Language Change: Dative Subjects in Icelandic,” in Proceedings of the LREC 2016 Workshop VisLRII: Visualization as Added Value in the Development, Use and Evaluation of Language Resources, in Proceedings of the LREC 2016 Workshop VisLRII: Visualization as Added Value in the Development, Use and Evaluation of Language Resources. 2016, pp. 8–15. [Online]. Available: http://www.lrec-conf.org/proceedings/lrec2016/workshops/LREC2016Workshop-VisLR%20II_Proceedings.pdf
    29. M. Herschel and M. Hlawatsch, “Provenance: On and Behind the Screens,” in Proceedings of the ACM International Conference on the Management of Data (SIGMOD), F. Özcan, G. Koutrika, and S. Madden, Eds., in Proceedings of the ACM International Conference on the Management of Data (SIGMOD). ACM, 2016, pp. 2213–2217. doi: 10.1145/2882903.2912568.
    30. V. Bruder, S. Frey, and T. Ertl, “Real-Time Performance Prediction and Tuning for Interactive Volume Raycasting,” in Proceedings of the SIGGRAPH Asia Symposium on Visualization, ACM, Ed., in Proceedings of the SIGGRAPH Asia Symposium on Visualization, vol. 2016. ACM, 2016, pp. 1–8. doi: 10.1145/3002151.3002156.
    31. T. Blascheck, F. Beck, S. Baltes, T. Ertl, and D. Weiskopf, “Visual analysis and coding of data-rich user behavior,” in IEEE Conference on Visual Analytics Science and Technology, in IEEE Conference on Visual Analytics Science and Technology. IEEE, 2016, pp. 141–150. doi: 10.1109/vast.2016.7883520.
    32. D. Maurer, Y.-C. Ju, M. Breuß, and A. Bruhn, “Combining shape from shading and stereo: a variational approach for the joint estimation of depth, illumination and albedo.,” in Proceedings of the British Machine Vision Conference (BMVC), in Proceedings of the British Machine Vision Conference (BMVC). BMVA Press, 2016.
    33. K. Kurzhals, M. Hlawatsch, F. Heimerl, M. Burch, T. Ertl, and D. Weiskopf, “Gaze Stripes: Image-Based Visualization of Eye Tracking Data,” IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 1, Art. no. 1, 2016, doi: 10.1109/TVCG.2015.2468091.
    34. R. Netzel, M. Burch, and D. Weiskopf, “User Performance and Reading Strategies for Metro Maps: An Eye Tracking Study,” Special Issue on Eye Tracking for Spatial Research in Spatial Cognition and Computation: An Interdisciplinary Journal, 2016, doi: 10.1080/13875868.2016.1226839.
    35. M. Burch, R. Woods, R. Netzel, and D. Weiskopf, “The Challenges of Designing Metro Maps,” Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016, doi: 10.5220/0005679601950202.
    36. V. Schwind and S. Jäger, “The Uncanny Valley and the Importance of Eye Contact,” in Mensch und Computer 2015 - Tagungsband, in Mensch und Computer 2015 - Tagungsband, vol. 2015. Oldenbourg Wissenschaftsverlag, 2016, pp. 153–162. doi: 10.1515/icom-2016-0001.
    37. R. Netzel, M. Burch, and D. Weiskopf, “Interactive Scanpath-Oriented Annotation of Fixations,” Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, pp. 183–187, 2016, doi: 10.1145/2857491.2857498.
    38. A. Barth and A. Stein, “Approximation and simulation of infinite-dimensional Lévy processes,” Stochastics and Partial Differential Equations: Analysis and Computations, vol. 6, no. 2, Art. no. 2, 2016, doi: 10.1007/s40072-017-0109-2.
    39. S. Funke, F. Krumpe, and S. Storandt, “Crushing Disks Efficiently,” in Combinatorial Algorithms. IWOCA 2016. Lecture Notes in Computer Science, vol. 9843, V. Mäkinen, S. J. Puglisi, and L. Salmela, Eds., in Combinatorial Algorithms. IWOCA 2016. Lecture Notes in Computer Science, vol. 9843. , Springer International Publishing, 2016, pp. 43–54. doi: 10.1007/978-3-319-44543-4_4.
    40. O. Johannsen, A. Sulc, N. Marniok, and B. Goldluecke, “Layered Scene Reconstruction from Multiple Light Field Camera Views,” in Computer Vision – ACCV 2016. ACCV 2016. Lecture Notes in Computer Science, vol. 10113, S.-H. Lai, V. Lepetit, K. Nishino, and Y. Sato, Eds., in Computer Vision – ACCV 2016. ACCV 2016. Lecture Notes in Computer Science, vol. 10113. , Springer International Publishing, 2016, pp. 3–18. doi: 10.1007/978-3-319-54187-7_1.
    41. T. Waltemate et al., “The Impact of Latency on Perceptual Judgments and Motor Performance in Closed-loop Interaction in Virtual Reality,” in Proceedings of the ACM Conference on Virtual Reality Software and Technology (VRST), D. Kranzlmüller and G. Klinker, Eds., in Proceedings of the ACM Conference on Virtual Reality Software and Technology (VRST). ACM, 2016, pp. 27–35. doi: 10.1145/2993369.2993381.
    42. J. Zagermann, U. Pfeil, and H. Reiterer, “Measuring Cognitive Load using Eye Tracking Technology in Visual Computing,” in Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV), M. Sedlmair, P. Isenberg, T. Isenberg, N. Mahyar, and H. Lam, Eds., in Proceedings of the Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (BELIV). ACM, 2016, pp. 78–85. doi: 10.1145/2993901.2993908.
    43. J. Hildenbrand, A. Nocaj, and U. Brandes, “Flexible Level-of-Detail Rendering for Large Graphs,” no. 9801, Y. Hu and M. Nöllenburg, Eds., 2016. [Online]. Available: https://link.springer.com/content/pdf/bbm%3A978-3-319-50106-2%2F1.pdf
    44. E. Wood, T. Baltrusaitis, L.-P. Morency, P. Robinson, and A. Bulling, “A 3D Morphable Eye Region Model for Gaze Estimation,” in Proceedings of the European Conference on Computer Vision (ECCV), in Proceedings of the European Conference on Computer Vision (ECCV). 2016, pp. 297–313. [Online]. Available: https://link.springer.com/chapter/10.1007%2F978-3-319-46448-0_18
    45. I. Zingman, D. Saupe, O. A. B. Penatti, and K. Lambers, “Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, Art. no. 8, 2016, [Online]. Available: https://ieeexplore.ieee.org/document/7452408
    46. S. Butscher and H. Reiterer, “Applying Guidelines for the Design of Distortions on Focus+Context Interfaces,” in Proceedings of the Working Conference on Advanced Visual Interfaces (AVI), P. Buono, R. Lanzilotti, M. Matera, and M. F. Costabile, Eds., in Proceedings of the Working Conference on Advanced Visual Interfaces (AVI). ACM, 2016, pp. 244–247. doi: 10.1145/2909132.2909284.
    47. R. Netzel and D. Weiskopf, “Hilbert Attention Maps for Visualizing Spatiotemporal Gaze Data,” in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS), in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS). 2016, pp. 21–25. [Online]. Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7851160
    48. A. Kumar, R. Netzel, M. Burch, D. Weiskopf, and K. Mueller, “Multi-Similarity Matrices of Eye Movement Data,” in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS), in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS). 2016, pp. 26–30. [Online]. Available: https://ieeexplore.ieee.org/document/7851161
    49. A. Voit, T. Machulla, D. Weber, V. Schwind, S. Schneegaß, and N. Henze, “Exploring Notifications in Smart Home Environments,” in Proceedings of the International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI), ACM, Ed., in Proceedings of the International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI). 2016, pp. 942–947. doi: 10.1145/2957265.2962661.
    50. S. Funke, A. Nusser, and S. Storandt, “On k-Path Covers and their Applications.,” VLDB Journal, vol. 25, no. 1, Art. no. 1, 2016, doi: 10.1007/s00778-015-0392-3.
    51. D. Saupe, F. Hahn, V. Hosu, I. Zingman, M. Rana, and S. Li, “Crowd Workers Proven Useful: A Comparative Study of Subjective Video Quality Assessment,” in Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX), in Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX). 2016, pp. 1–2. [Online]. Available: https://www.uni-konstanz.de/mmsp/pubsys/publishedFiles/SaHaHo16.pdf
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  11. 2015

    1. T. Chandler et al., “Immersive Analytics,” Sep. 2015, IEEE. doi: 10.1109/bdva.2015.7314296.
    2. L. L. Chuang and H. H. Bülthoff, “Towards a Better Understanding of Gaze Behavior in the Automobile,” in Position papers of the workshops at AutomotiveUI’15, in Position papers of the workshops at AutomotiveUI’15. Sep. 2015. [Online]. Available: https://www.auto-ui.org/15/p/workshops/2/8_Towards%20a%20Better%20Understanding%20of%20Gaze%20Behavior%20in%20the%20Automobile_Chuang.pdf
    3. M. Spicker, J. Kratt, D. Arellano, and O. Deussen, “Depth-aware Coherent Line Drawings,” in Proceedings of the SIGGRAPH Asia Symposium on Computer Graphics and Interactive Techniques, Technical Briefs, in Proceedings of the SIGGRAPH Asia Symposium on Computer Graphics and Interactive Techniques, Technical Briefs. ACM, 2015, pp. 1:1-1:5. doi: 10.1145/2820903.2820909.
    4. L. Lischke et al., “Using Space: Effect of Display Size on Users’ Search Performance,” in Proceedings of the CHI Conference on Human Factors in Computing Systems-Extended Abstracts (CHI-EA), B. Begole, J. Kim, K. Inkpen, and W. Woo, Eds., in Proceedings of the CHI Conference on Human Factors in Computing Systems-Extended Abstracts (CHI-EA). ACM, 2015, pp. 1845–1850. doi: 10.1145/2702613.2732845.
    5. S. Frey, F. Sadlo, and T. Ertl, “Balanced Sampling and Compression for Remote Visualization,” in Proceedings of the SIGGRAPH Asia Symposium on High Performance Computing, in Proceedings of the SIGGRAPH Asia Symposium on High Performance Computing. ACM, 2015, pp. 1–4. doi: 10.1145/2818517.2818529.
    6. M. Sedlmair and M. Aupetit, “Data-driven Evaluation of Visual Quality Measures,” Computer Graphics Forum, vol. 34, no. 3, Art. no. 3, 2015, doi: 10.5555/2858877.2858899.
    7. L. L. Chuang, “Error Visualization and Information-Seeking Behavior for Air-Vehicle Control,” in Foundations of Augmented Cognition. AC 2015. Lecture Notes in Computer Science, vol. 9183, D. Schmorrow and C. M. Fidopiastis, Eds., in Foundations of Augmented Cognition. AC 2015. Lecture Notes in Computer Science, vol. 9183. , Springer, 2015, pp. 3–11. doi: 10.1007/978-3-319-20816-9_1.
    8. L. Lischke, P. Knierim, and H. Klinke, “Mid-Air Gestures for Window Management on Large Displays,” in Mensch und Computer 2015 – Tagungsband (MuC), D. G. Oldenbourg, Ed., in Mensch und Computer 2015 – Tagungsband (MuC). De Gruyter, 2015, pp. 439–442. doi: 10.1515/9783110443929-072.
    9. K. Kurzhals, M. Burch, T. Pfeiffer, and D. Weiskopf, “Eye Tracking in Computer-based Visualization,” Computing in Science & Engineering, vol. 17, no. 5, Art. no. 5, 2015, doi: 10.1109/MCSE.2015.93.
    10. C. Schulz, M. Burch, and D. Weiskopf, “Visual Data Cleansing of Eye Tracking Data,” in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS), in Proceedings of the Symposium on Eye Tracking and Visualization (ETVIS). 2015. [Online]. Available: http://etvis.visus.uni-stuttgart.de/etvis2015/papers/etvis15_schulz.pdf
    11. M. Hund et al., “Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion,” in Similarity Search and Applications. International Conference on Similarity Search and Applications (SISAP). Lecture Notes in Computer Science, vol. 9371, G. Amato, R. Connor, F. Falchi, and C. Gennaro, Eds., in Similarity Search and Applications. International Conference on Similarity Search and Applications (SISAP). Lecture Notes in Computer Science, vol. 9371. , Springer, Cham, 2015, pp. 307–313. [Online]. Available: https://link.springer.com/chapter/10.1007%2F978-3-319-25087-8_29
    12. L. Lischke, J. Grüninger, K. Klouche, A. Schmidt, P. Slusallek, and G. Jacucci, “Interaction Techniques for Wall-Sized Screens,” Proceedings of the International Conference on Interactive Tabletops & Surfaces (ITS), pp. 501–504, 2015, doi: 10.1145/2817721.2835071.
    13. N. Flad, T. Fomina, H. H. Bülthoff, and L. L. Chuang, “Unsupervised Clustering of EOG as a Viable Substitute for Optical Eye Tracking,” in Eye Tracking and Visualization: Foundations, Techniques, and Applications, M. Burch, L. L. Chuang, B. D. Fisher, A. Schmidt, and D. Weiskopf, Eds., in Eye Tracking and Visualization: Foundations, Techniques, and Applications. , Springer International Publishing, 2015, pp. 151–167. doi: 10.1007/978-3-319-47024-5_9.

Project Group A

Models and Measures

 

Completed

 

Project Group B

Adaptive Algorithms

 

Completed

 

Project Group C

Interaction

 

Completed

 

Project Group D

Applications

 

Completed