How can typical problems and regularities in image sequences be detected reliably and how can they be quantified numerically?
How can this information be used to rate the difficulty of video sequences, e.g. for assessing benchmarks and for modeling algorithms?
To what extent can priors be learned for different types of problems and regularities?
To what extent can adaptive approaches be designed that are able to handle challenging real-world scenarios based on previously learned priors and decision algorithms?