Tracking multiple objects under occlusion is one of the most challenging issues in computer vision. Occlusion results in mistaken match when finding the most similar candidate. A...
Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weimin...
In this paper, we introduce a novel probabilistic approach to handle occlusions and perspective effects. The proposed method is an object based method embedded in a marked point p...
Ahmed Gamal-Eldin, Xavier Descombes, Josiane Zerub...
Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm...
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
Abstract. We propose a novel and efficient method for generic arbitraryview object class detection and localization. In contrast to existing singleview and multi-view methods using...
Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, Long Q...