We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
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...
Detecting and segmenting free-form objects from cluttered backgrounds is a challenging problem in computer vision. Signature detection in document images is one classic example an...
Guangyu Zhu, Yefeng Zheng, David S. Doermann, Stef...
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Visual tracking is a very important front-end to many vision applications. We present a new framework for robust visual tracking in this paper. Instead of just looking forward in ...
Hao Wu, Rama Chellappa, Aswin C. Sankaranarayanan,...