We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
The goal of this work is to find all people in archive films. Challenges include low image quality, motion blur, partial occlusion, non-standard poses and crowded scenes. We base ...
We develop a pairwise classification framework for face recognition, in which a class face recognition problem is divided into a set of ? ?? ? two class problems. Such a problem...
Feature-based object classification, which distinguish a moving object to human or vehicle, is important in visual surveillance. In order to improve classification performance, in...