This paper proposes a novel approach for multi-view multi-pose object detection using discriminative shapebased exemplars. The key idea underlying this method is motivated by nume...
Ying Shan, Feng Han, Harpreet S. Sawhney, Rakesh K...
Viewpoint invariant pedestrian recognition is an important yet under-addressed problem in computer vision. This is likely due to the difficulty in matching two objects with unknown...
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...