In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
Most existing methods of stereo matching focus on dealing with clear image pairs. Consequently, there is a lack of approaches capable of handling degraded images captured under ch...
In this paper, a novel framework for face recognition based on discriminatively trained orthogonal rank-one tensor projections (ORO) and local binary pattern (LBP) is proposed. LB...
In this paper, we present a least square kernel machine with box constraints (LSKMBC). The existing least square machines assume Gaussian hyperpriors and subsequently express the ...
Training a classifier for object category recognition using images on the Internet is an attractive approach due to its scalability. However, a big challenge in this approach is ...