We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
In this paper we study the problem of online aligning a newly arrived image to previously well-aligned images. Inspired by recent advances in batch image alignment using low rank ...
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
We propose a data-driven, hierarchical approach for the analysis of human actions in visual scenes. In particular, we focus on the task of in-house assisted living. In such scenar...
We present a change detection method resistant to global and local illumination variations for use in visual surveillance scenarios. Approaches designed thus far for robustness to...