We study the challenging problem of maneuvering object tracking with unknown dynamics, i.e., forces or torque. We investigate the underlying causes of object kinematics, and propo...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
We present a higher-level visual representation, visual synset, for object categorization. The visual synset improves the traditional bag of words representation with better discr...
Yantao Zheng, Ming Zhao 0003, Shi-Yong Neo, Tat-Se...
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
In this paper, the problem of estimating automatically the symmetry plane of bilateral objects (having perfect or imperfect mirror symmetry) in point clouds is reexamined. Classic...