1. J. Goertler, C. Schulz, O. Deussen, and D. Weiskopf, “Bubble Treemaps for Uncertainty Visualization,” IEEE Transactions on Visualization and Computer Graphics, 2018.
  2. S. Frey, “Sampling and Estimation of Pairwise Similarity in Spatio-Temporal Data Based on Neural Networks,” in Informatics, 2017, vol. 4, no. 3, p. 27.
  3. V. Schwind, K. Wolf, and N. Henze, “FaceMaker - A Procedural Face Generator to Foster Character Design Research,” vol. Game Dynamics: Best Practices in Procedural and Dynamic Game Content Generation, O. Korn and N. Lee, Eds. Cham: Springer International Publishing, 2017, pp. 95–113.
  4. R. Netzel, M. Hlawatsch, M. Burch, S. Balakrishnan, H. Schmauder, and D. Weiskopf, “An Evaluation of Visual Search Support in Maps,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, 2017.
  5. P. Tutzauer and N. Haala, “Processing of crawled urban imagery for building use classification,” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci, XLII-1/W1, pp. 143–149, 2017.
  6. V. Hosu, F. Hahn, M. Jenadeleh, H. M. Lin, S. H., S. T., Li, and D. Saupe, “The Konstanz natural video database (KoNViD-1k),” in 9th International Conference on Quality of Multimedia Experience (QoMEX), 2017.
  7. K. Kurzhals, M. Hlawatsch, C. Seeger, and D. Weiskopf, “Visual Analytics for Mobile Eye Tracking,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, 2017.
  8. M. Krone, F. Frieß, K. Scharnowski, G. Reina, S. Fademrecht, T. Kulschewski, J. Pleiss, and T. Ertl, “Molecular Surface Maps,” IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Scientific Visualization 2016), vol. 23, no. 1, 2017.
  9. V. Schwind, P. Knierim, C. Tasci, P. Franczak, N. Haas, and N. Henze, “These Are Not My Hands!": Effect of Gender on the Perception of Avatar Hands in Virtual Reality,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, 2017, vol. CHI '17, no. 6, pp. 1577–1582.
  10. D. Sacha, M. Kraus, J. Bernard, M. Behrisch, T. Schreck, Y. Asano, and D. A. Keim, “SOMFlow: Guided exploratory cluster analysis with self-organizing maps and analytic provenance,” IEEE Conference on Visual Analytics Science and Technology, 2017.
  11. S. Frey and T. Ertl, “Progressive Direct Volume-to-Volume Transformation.,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 921–930, 2017.
  12. K. Kurzhals, E. Çetinkaya, Y. Hu, W. Wang, and D. Weiskopf, “Close to the Action: Eye-Tracking Evaluation of Speaker-Following Subtitles,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017.
  13. K. de Winkel, A. Nesti, H. Ayaz, and H. Bülthoff, “Neural correlates of decision making on whole body yaw rotation: an fNIRS study,” Neuroscience Letters, 2017.
  14. C. Schätzle, M. Hund, F. L. Dennig, M. Butt, and D. A. Keim, “HistoBankVis: Detecting Language Change via Data Visualization.,” in Proceedings of the NoDaLiDa 2017 Workshop on Processing Historical Language, 2017, no. 133, pp. 32–39.
  15. D. Maurer, M. Stoll, S. Volz, P. Gairing, and A. Bruhn, “A comparison of isotropic and anisotropic second order regularisers for optical flow.,” in International Conference on Scale Space and Variational Methods in Computer Vision (SSVM)., Berlin, 2017, vol. Lecture Notes in Computer Science, no. 10302, pp. 537–549.
  16. D. Maurer, M. Stoll, and A. Bruhn, “Order-adaptive and illumination-aware variational optical flow refinement,” in British Machine Vision Conference (BMVC), 2017.
  17. P. Knierim, T. Kosch, V. Schwind, M. Funk, F. Kiss, S. Schneegass, and N. Henze, “Tactile Drones - Providing Immersive Tactile Feedback in Virtual Reality Through Quadcopters,” in Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, 2017, vol. CHI EA '17, pp. 433–436.
  18. S. Egger-Lampl, J. Redi, T. Hofeld, M. Hirth, S. Möller, B. Naderi, C. Keimel, and D. Saupe, “Dagstuhl Seminar 15481, Dagstuhl Castle, Germany, November 22 – 27, 2015, Revised Contributions,” in Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments, vol. Information Systems and Applications, incl. Internet/Web, and HCI, no. 10264, D. Archambault, H. Purchase, and T. Hossfeld, Eds. Springer International Publishing, 2017, pp. 173 – 212.
  19. V. Schwind, P. Knierim, L. Chuang, and N. Henze, “Where’s Pinky?": The Effects of a Reduced Number of Fingers in Virtual Reality,” in Proceedings of the 2017 CHI Conference on Computer-Human Interaction in Play, New York, NY, USA, 2017, vol. CHI PLAY'17, p. 6.
  20. K. Srulijes, C. Schulz, D. J. Mack, R. Jarosch, J. Klenk, L. Schwickert, M. Schwenk, W. Maetzler, D. Weiskopf, and C. Becker, “Visualization of eye-head coordination while walking in healthy subjects and patients with neurodegenerative diseases.” 2017.
  21. H. Ben Lahmar and M. Herschel, “Provenance-based Recommendations for Visual Data Exploration,” in International Workshop on Theory and Practice of Provenance (TAPP), 2017.
  22. M. van Garderen, B. Pampel, A. Nocaj, and U. Brandes, “Minimum-Displacement Overlap Removal for Geo-referenced Data Visualization,” The Author(s) Computer Graphics Forum, vol. 36, no. 3, pp. 423–433, 2017.
  23. M. Heinemann, V. Bruder, S. Frey, and T. Ertl, “Power Efficiency of Volume Raycasting on Mobile Devices,” in EuroVis 2017 - Posters, 2017.
  24. L. Merino, J. Fuchs, M. Blumenschein, C. Anslow, M. Ghafari, O. Nierstrasz, B. M., and D. A. Keim, “On the Impact of the Medium in the Effectiveness of 3D Software Visualizations,” in VISSOFT’17: Proceedings of the 5th IEEE Working Conference on Software Visualization, 2017.
  25. M. Stoll, S. Volz, D. Maurer, and A. Bruhn, “A time-efficient optimisation framework for parameters of optical flow methods,” in Scandinavian Conference on Image Analysis (SCIA)., Berlin, 2017, vol. Lecture Notes in Computer Science, no. 10269, pp. 41–53.
  26. K. Kurzhals, M. Stoll, A. Bruhn, and D. Weiskopf, “FlowBrush: Optical Flow Art,” in Proceedings of Computational Aesthetics 2017, 2017.
  27. D. Maurer, M. Stoll, and A. Bruhn, “Order-adaptive regularisation for variational optical flow: global, local and in between,” in International Conference on Scale Space and Variational Methods in Computer Vision (SSVM)., Berlin, 2017, vol. Lecture Notes in Computer Science, no. 10302, pp. 550–562.
  28. J. Zagermann, U. Pfeil, D. Fink, P. von Bauer, and H. Reiterer, “Memory in Motion: The Influence of Gesture- and Touch-Based Input Modalities on Spatial Memory,” 2017.
  29. N. Rodrigues, R. Netzel, K. R. Ullah, M. Burch, A. Schultz, B. Burger, and D. Weiskopf, “Visualization of Time Series Data with Spatial Context: Communicating the Energy Production of Power Plants,” in VINCI 2017, 2017.
  30. N. Rodrigues and D. Weiskopf, “Nonlinear Dot Plots,” IEEE Transactions on Visualization and Computer Graphics, vol. 2018, 2017.
  31. N. Rodrigues, M. Burch, L. Di Silvestro, and D. Weiskopf, “A Visual Analytics Approach for Word Relevances in Multiple Texts,” in IV 2017, 2017.
  32. M. Spicker, F. Hahn, T. Lindemeier, D. Saupe, and O. Deussen, “Quantifying Visual Abstraction Quality for Stipple Drawings,” in Proceedings of NPAR’17, 2017.
  33. M. Herschel, R. Diestelkämper, and H. Ben Lahmar, “A survey on provenance - What for? What form? What from?,” the International Journal on Very Large Data Bases (VLDB Journal), 2017.
  34. M. A. Baazizi, H. Ben Lahmar, D. Colazzo, G. Ghelli, and C. Sartiani, “Schema Inference for Massive JSON Datasets,” in Conference on Extending Database Technology (EDBT), 2017, pp. 222–233.
  35. P. Gralka, C. Schulz, G. Reina, D. Weiskopf, and T. Ertl, “Visual Exploration of Memory Traces and Call Stacks,” VISSOFT 2017, 2017.
  36. G. Tkachev, S. Frey, C. Müller, V. Bruder, and T. Ertl, “Prediction of Distributed Volume Visualization Performance to Support Render Hardware Acquisition,” Eurographics Symposium on Parallel Graphics and Visualization, 2017.
  37. J. Karolus, P. W. Woźniak, L. L. Chuang, and A. Schmidt, “Robust Gaze Features for Enabling Language Proficiency Awareness,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI ’17), New York, NY, USA, 2017, pp. 2998–3010.
  38. M. Stein, H. Janetzko, A. Lamprecht, T. Breitkreutz, P. Zimmermann, B. Goldlücke, T. Schreck, G. Andrienko, M. Grossniklaus, and D. A. Keim, “Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.,” in IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visual Analytics Science and Technology), 2017.
  39. M. Burch, M. Hlawatsch, and D. Weiskopf, “Visualizing a Sequence of a Thousand Graphs (or Even More),” Computer Graphics Forum, vol. 36, no. 3, 2017.
  40. J. Iseringhausen, B. Goldlücke, N. Pesheva, S. Iliev, A. Wender, M. Fuchs, and M. B. Hullin, “4D Imaging through Spray-On Optics,” ACM Transactions on Graphics (SIGGRAPH 2017), vol. 36, no. 4, pp. 35:1–35:11, 2017.
  41. J. Kratt, F. Eisenkeil, M. Spicker, Y. Wang, D. Weiskopf, and O. Deussen, “Structure-aware Stylization of Mountainous Terrains,” in Vision, Modeling & Visualization, 2017.
  42. R. Diestelkämper, M. Herschel, and P. Jadhav, “Provenance in DISC Systems: Reducing Space Overhead at Runtime,” in International Workshop on Theory and Practice of Provenance (TAPP), 2017.
  43. U. Gadiraju, S. Möller, M. Nöllenburg, D. Saupe, S. Egger-Lamperl, D. Archambault, and B. Fisher, “Crowdsourcing versus the laboratory: Towards human-centered experiments using the crowd,” in Information Systems and Applications, incl. Internet/Web, and HCI, vol. Evaluation in the Crowd. Crowdsourcing and Human-Centered Experiments, no. 10264, D. Archambault, H. Purchase, and T. Hossfeld, Eds. Springer International Publishing, 2017, pp. 7 – 30.
  44. D. Jäckle, M. Hund, M. Behrisch, D. A. Keim, and T. Schreck, “Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces,” in IEEE Conference on Visual Analytics Science and Technology (VAST), 2017.
  45. C. Schulz, M. Burch, F. Beck, and D. Weiskopf, “Visual Data Cleansing of Low-Level Eye Tracking Data,” in Eye Tracking and Visualization: Foundations, Techniques, and Applications. ETVIS 2015, M. Burch, L. Chuang, B. Fisher, A. Schmidt, and D. Weiskopf, Eds. Springer International Publishing, 2017.
  46. M. Krone, F. Frieß, K. Scharnowski, G. Reina, S. Fademrecht, T. Kulschewski, J. Pleiss, and T. Ertl, “Molecular Surface Maps,” in IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Scientific Visualization 2016), 2017, vol. 23, no. 1.
  47. D. Jäckle, F. Stoffel, S. Mittelstädt, D. A. Keim, and H. Reiterer, “Interpretation of Dimensionally-Reduced Crime Data: A Study with Untrained Domain Experts.,” in Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Best Student Paper Award, 2017, no. 3, pp. 164–175.
  48. A. Nesti, K. de Winkel, and H. Bülthoff, “Accumulation of inertial sensory information in the perception of whole body yaw rotation,” One, Plos, 2017.
  49. C. Schulz, A. Nocaj, J. Goertler, O. Deussen, U. Brandes, and D. Weiskopf, “Probabilistic Graph Layout for Uncertain Network Visualization,” vol. 23, no. 1, 2017.
  50. R. Netzel and D. Weiskopf, “Hilbert Attention Maps for Visualizing Spatiotemporal Gaze Data,” 2016.
  51. C. Schätzle and D. Sacha, “Visualizing Language Change: Dative Subjects in Icelandic,” in Proceedings of the Language Resources and Evaluation Conference 2016 (Workshop “VisLRII: Visualization as Added Value in the Development, Use and Evaluation of Language Resources,” 2016, pp. 8–15.
  52. S. Frey and T. Ertl, “Auto-tuning intermediate representations for in situ visualization,” in Scientific Data Summit (NYSDS), 2016 New York, 2016, pp. 1–10.
  53. J. Karolus, P. W. Woźniak, and L. L. Chuang, “Towards Using Gaze Properties to Detect Language Proficiency,” in Proceedings of the 9th Nordic Conference on Human-Computer Interaction (NordiCHI ’16), New York, NY, USA, 2016, no. 118, p. 6.
  54. K. Kurzhals, M. Hlawatsch, M. Burch, and D. Weiskopf, “Fixation-Image Charts,” in Proceedings of the Symposium on Eye Tracking Research & Applications, 2016, vol. 1.
  55. A. Voit, T. Machulla, D. Weber, V. Schwind, S. Schneegass, and N. Henze, “Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct - MobileHCI ’16,” in Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct - MobileHCI ’16, 2016, pp. 942–947.
  56. C. Schulz, A. Nocaj, M. El-Assady, S. Frey, M. Hlawatsch, M. Hund, G. K. Karch, R. Netzel, C. Schätzle, M. Butt, D. A. Keim, T. Ertl, U. Brandes, and D. Weiskopf, “Generative Data Models for Validation and Evaluation of Visualization Techniques,” in BELIV ’16: Beyond Time And Errors: Novel Evaluation Methods For Visualization, 2016.
  57. 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, 2016.
  58. 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, 2016.
  59. L. Lischke, V. Schwind, K. Friedrich, A. Schmidt, and N. Henze, “MAGIC-Pointing on Large High-Resolution Displays,” in CHI EA ’16 Proceedings of the 34rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, 2016, pp. 1706–1712.
  60. 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 2016 ACM International Symposium on Wearable Computers - ISWC ’16, New York, New York, USA, 2016, pp. 116–119.
  61. V. Hosu, F. Hahn, O. Wiedemann, S.-H. Jung, and D. Saupe, “Saliency-driven image coding improves overall perceived JPEG quality,” in Picture Coding Symposium (PCS), 2016.
  62. M. Herschel and M. Hlawatsch, “Provenance: On and Behind the Screens.,” in ACM International Conference on the Management of Data (SIGMOD), 2016, pp. 2213–2217.
  63. A. Kumar, R. Netzel, M. Burch, D. Weiskopf, and K. Mueller, “Multi-Similarity Matrices of Eye Movement Data,” 2016.
  64. S. Frey and T. Ertl, “Flow-Based Temporal Selection for Interactive Volume Visualization,” in Computer Graphics Forum, 2016.
  65. V. Schwind and S. Jäger, “The Uncanny Valley and the Importance of Eye Contact.,” i-com, vol. 15, no. 1, pp. 93–104, 2016.
  66. V. Bruder, S. Frey, and T. Ertl, “Real-Time Performance Prediction and Tuning for Interactive Volume Raycasting,” in SIGGRAPH ASIA 2016 Symposium on Visualization, 2016, vol. 2016, no. 7.
  67. 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.
  68. L. Lischke, S. Mayer, K. Wolf, N. Henze, H. Reiterer, and A. Schmidt, “Screen arrangements and interaction areas for large display work places.,” vol. Proceedings of the 5th ACM International Symposium on Pervasive Displays PerDis 2016, pp. 228–234, 2016.
  69. M. Hund, D. Böhm, W. Sturm, M. Sedlmair, T. Schreck, T. Ullrich, D. A. Keim, L. Majnaric, and A. Holzinger, “Visual analytics for concept exploration in subspaces of patient groups.,” Brain Informatics, vol. 3, no. 4, pp. 233–247, 2016.
  70. M. Behrisch, B. Bach, M. Hund, L. von Rüden, M. Delz, J.-D. Fekete, and T. Schreck, “Magnostics: Image-based Search of Interesting Matrix Views for Guided Network Exploration.,” 2016, vol. 23, no. 1–1, p. 99.
  71. I. Zingman, D. Saupe, O. Penatti, and K. Lambers, “Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images,” 2016.
  72. K. Kurzhals, M. Hlawatsch, M. Burch, and D. Weiskopf, “Fixation-Image Charts,” in ETRA, 2016, vol. Proceedings of the Symposium on Eye Tracking Research & Applications, no. 1, pp. 11–18.
  73. 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,” 8th International Conference on Quality of Multimedia Experience (QoMEX 2016), Lisbon, Portugal, 2016.
  74. C. Schulz, A. Nocaj, M. El-Assady, S. Frey, M. Hlawatsch, M. Hund, G. K. Karch, R. Netzel, C. Schätzle, M. Butt, D. A. Keim, T. Ertl, U. Brandes, and D. Weiskopf, “Generative Data Models for Validation and Evaluation of Visualization Techniques.,” in BELIV Workshop 2016, 2016, pp. 112–124.
  75. D. Weiskopf, M. Burch, L. L. Chuang, B. Fischer, and A. Schmidt, Eye Tracking and Visualization: Foundations, Techniques, and Applications. Berlin, Heidelberg: Springer, 2016.
  76. T. Blascheck, F. Beck, S. Baltes, T. Ertl, and D. Weiskopf, “Visual Analysis and Coding of Data-Rich User Behavior,” 2016.
  77. J. Zagermann, U. Pfeil, and H. Reiterer, “Measuring Cognitive Load using Eye Tracking Technology in Visual Computing,” 2016, vol. Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization (BELIV 2016), pp. 78–85.
  78. R. Netzel, M. Burch, and D. Weiskopf, “Interactive Scanpath-Oriented Annotation of Fixations,” 2016, pp. 183–187.
  79. C. Schulz, M. Burch, F. Beck, and D. Weiskopf, “Visual Data Cleansing of Low-Level Eye Tracking Data,” in Extended Papers of ETVIS 2015, 2016.
  80. A. Hautli-Janisz and V. Lyding, “VisLR II: Visualization as Added Value in the Development, Use and Evaluation of Language Resources,” in Proceedings of the Language Resources and Evaluation Conference 2016 (Workshop “VisLRII: Visualization as Added Value in the Development, Use and Evaluation of Language Resources,” 2016, pp. 8–15.
  81. 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, pp. 1662–1671, 2016.
  82. P. Tutzauer, S. Becker, T. Niese, O. Deussen, and D. Fritsch, “Understanding Human Perception of Building Categories in Virtual 3d Cities - a User Study,” ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLI–B2, pp. 683–687, 2016.
  83. J. Hildenbrand, A. Nocaj, and U. Brandes, “Flexible Level-of-Detail Rendering for Large Graphs,” no. 9801 2016, G. Drawing and 24th International Symposium Network Visualization, Eds. 2016.
  84. 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, no. 5–6, pp. 319–333(15), 2016.
  85. M. Hund, I. Färber, M. Behrisch, A. Tatu, T. Schreck, D. A. Keim, and T. Seidl, “Visual Quality Assessment of Subspace Clusterings,” in KDD 2016 Interactive Data Exploration and Analytics (IDEA), 2016.
  86. V. Hosu, F. Hahn, I. Zingman, and D. Saupe, “Reported Attention as a Promising Alternative to Gaze in IQA Tasks,” 5th International Workshop on Perceptual Quality of Systems 2016 (PQS 2016), Berlin, 2016.
  87. O. Johannsen, A. Sulc, N. Marniok, and B. Goldluecke, “Layered scene reconstruction from multiple light field camera views,” 2016.
  88. M. Burch, R. Woods, R. Netzel, and D. Weiskopf, “The Challenges of Designing Metro Maps,” 2016, pp. 195–202.
  89. N. Flad, J. Ditz, H. H. Bülthoff, and L. L. Chuang, “Data-driven approaches to unrestricted gaze-tracking benefit from saccade filtering,” Second Workshop on Eye Tracking and Visualization, IEEE Visualization 2016, 2016.
  90. K. Kurzhals, M. Burch, T. Pfeiffer, and D. Weiskopf, “Eye Tracking in Computer-Based Visualization,” Computing in Science & Engineering, vol. 17, no. 5, 2015.
  91. C. Schulz, M. Burch, and D. Weiskopf, “Visual Data Cleansing of Eye Tracking Data,” in Eye Tracking and Visualization (Proceedings of ETVIS 2015), 2015.
  92. S. Frey, F. Sadlo, and T. Ertl, “Balanced sampling and compression for remote visualization,” in SIGGRAPH Asia 2015 Visualization in High Performance Computing, 2015, pp. 1;1–4.
  93. L. Lischke, P. Knierim, and H. Klinke, “Mid-Air Gestures for Window Management on Large Displays,” in Mensch und Computer 2015 - Tagungsband, Berlin, München, Boston, 2015, pp. 439–442.
  94. L. Lischke, J. Grüninger, K. Klouche, A. Schmidt, P. Slusallek, and G. Jacucci, “Interaction Techniques for Wall-Sized Screens,” in Proceedings of the 2015 International Conference on Interactive Tabletops & Surfaces - ITS ’15, 2015, pp. 501–504.
  95. K. Kurzhals, B. Fisher, M. Burch, and D. Weiskopf, “Eye Tracking Evaluation of Visual Analytics,” Information Visualization, 2015.
  96. C. Schulz, M. Burch, and D. Weiskopf, Visual Data Cleansing of Eye Tracking Data. 2015.
  97. C. L. L. and B. H. H., “Towards a Better Understanding of Gaze Behavior in the Automobile.,” in Workshop on Practical Experiences in Measuring and Modeling Drivers and Driver-Vehicle Interactions In conjunction with AutomotiveUI 2015, 2015.
  98. L. L. Chuang, “Error visualization and information-seeking behavior for air-vehicle control.,” Foundations of Augmented Cognition. Lecture Notes in Artificial Intelligence, vol. 9183, pp. 3–11, 2015.
  99. N. Flad, T. Fomina, H. H. Bülthoff, and L. L. Chuang, “In press: Unsupervised clustering of EOG as a viable substitute for optical eye-tracking,” First Workshop on Eye Tracking and Visualization at IEEE Visualization, 2015.
  100. K. Kurzhals, B. Fisher, M. Burch, and D. Weiskopf, “Eye Tracking Evaluation of Visual Analytics,” 2015.