This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative ...
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...
We describe automated methods for constructing nonisomorphism proofs for pairs of graphs. The proofs can be human-readable or machinereadable. We have developed an experimental imp...
Arjeh M. Cohen, Jan Willem Knopper, Scott H. Murra...
Skimming or browsing audio recordings is much more difficult than visually scanning a document because of the temporal nature of audio. By exploiting properties of spontaneous spe...
Social interactions unfold over time, at multiple time scales, and can be observed through multiple sensory modalities. In this paper, we propose a machine learning framework for ...
Ian R. Fasel, Masahiro Shiomi, Pilippe-Emmanuel Ch...