We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
In this study we seek a fast method for robust, boundary preserving estimation of optical flow. Several studies have addressed this topic and proposed methods that account for vel...
— As cameras and storage devices have become cheaper, the number of video surveillance systems has also increased. Video surveillance was (and mostly is) done by human operators ...
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...