This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
We present a novel representation of shape for closed planar contours explicitly designed to possess a linear structure. This greatly simplifies linear operations such as averagin...
Alessandro Duci, Anthony J. Yezzi, Sanjoy K. Mitte...
This paper presents a multi-scale generative model for representing animate shapes and extracting meaningful parts of objects. The model assumes that animate shapes (2D simple clo...
Ego-motion estimation for an agile single camera moving through general, unknown scenes becomes a much more challenging problem when real-time performance is required rather than ...
Our paper addresses the problem of enforcing constraints in human body tracking. A projection technique is derived to impose kinematic constraints on independent multi-body motion...
We present a computational framework capable of labeling the effort of an action corresponding to the perceived level of exertion by the performer (low ? high). The approach initi...
A new algorithm is proposed for novel view generation in one-toone teleconferencing applications. Given the video streams acquired by two cameras placed on either side of a comput...
Antonio Criminisi, Jamie Shotton, Andrew Blake, Ph...
This paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. Our hypothesis is t...