Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
Graph cut is a popular technique for interactive image segmentation. However, it has certain shortcomings. In particular, graph cut has problems with segmenting thin elongated obj...
Computational color constancy is the task of estimating the true reflectances of visible surfaces in an image. In this paper we follow a line of research that assumes uniform illu...
Peter V. Gehler, Carsten Rother, Andrew Blake, Tho...
In recent years, local pattern based object detection and recognition have attracted increasing interest in computer vision research community. However, to our best knowledge no p...
Yadong Mu, Shuicheng Yan, Yi Liu, Thomas S. Huang,...
Recognizing people in images is one of the foremost challenges in computer vision. It is important to remember that consumer photography has a highly social aspect. The photograph...
Sparse features have traditionally been tracked from frame to frame independently of one another. We propose a framework in which features are tracked jointly. Combining ideas fro...
Given an object model and a black-box measure of similarity between the model and candidate targets, we consider visual object tracking as a numerical optimization problem. During...