We present in this paper a novel object tracking system based on 3D contour models. For this purpose, we integrate two complimentary likelihoods, defined on local color statistics...
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
The paper first traces the image-based modeling back to feature tracking and factorization that have been developed in the group led by Kanade since the eighties. Both feature tra...
In this paper, we show how to estimate, accurately and efficiently, the 3D motion of a rigid or non-rigid object, and time-varying lighting in a dynamic scene. This is achieved i...