Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
In this paper we propose an approach capable of simultaneous recognition and localization of multiple object classes using a generative model. A novel hierarchical representation ...
Extraction and matching of discriminative feature points in images is an important problem in computer vision with applications in image classification, object recognition, mosaici...
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
We present a robust anisotropic dense disparity estimation algorithm which employs perceptual maximum variation modeling. Edge-preserving dense disparity vectors are estimated usi...