We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
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...
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
State-of-the-art object retrieval systems are mostly based on the bag-of-visual-words representation which encodes local appearance information of an image in a feature vector. A ...