We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which impl...
An efficient Nonparametric Belief Propagation (NBP) algorithm is developed in this paper. While the recently proposed nonparametric belief propagation algorithm has wide applicati...
We present an extremely simple yet robust multi-view stereo algorithm and analyze its properties. The algorithm first computes individual depth maps using a window-based voting ap...
Multi-scale representations are motivated by the scale invariant properties of natural images. While many low level statistical measures, such as the local mean and variance of in...
This paper introduces a novel kernel-based method for template tracking in video sequences. The method is derived for a general warping transformation, and its application to affi...
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
We present an attempt to determine whether the shape of a generic central-projection camera, such as the eye of an insect or a log-polar camera, can be determined from two motion ...
Image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundame...