In this paper, we address the problem of detecting pedestrians in crowded real-world scenes with severe overlaps. Our basic premise is that this problem is too difficult for any t...
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Many sources of information relevant to computer vision and machine learning tasks are often underused. One example is the similarity between the elements from a novel source, suc...
We introduce a novel probabilistic approach for nonparametric nonrigid image registration using generalized elastic nets, a model previously used for topographic maps. The idea of...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...