Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
Due to the lack of explicit spatial consideration, existing
epitome model may fail for image recognition and target detection,
which directly motivates us to propose the so-calle...
Xinqi Chu, Shuicheng Yan, Liyuan Li, Kap Luk Chan,...
The lack of adequate training samples and the considerable variations observed in the available image collections due to aging, illumination and pose variations are the two key te...
Jie Wang, Kostas N. Plataniotis, Juwei Lu, Anastas...
Aiming at the problem when both positive and negative training set are enormous, this paper proposes a novel Matrix-Structural Learning (MSL) method, as an extension to Viola and ...