Human pose estimation is the task of determining the states (location, orientation and scale) of each body part. It is important for many vision understanding applications, e.g. v...
A new problem of retrieving social games from unstructured videos is proposed. Social games are characterized by repetitions (with variations) of alternating turns between two pla...
We present an algorithm that quickly and accurately estimates vanishing points in images of man-made environments. Contrary to previously proposed solutions, ours is neither itera...
Deformable model fitting has been actively pursued in the computer vision community for over a decade. As a result, numerous approaches have been proposed with varying degrees of ...
Action recognition methods suffer from many drawbacks in practice, which include (1)the inability to cope with incremental recognition problems; (2)the requirement of an intensive...
In this paper, we present an algorithm for occlusion boundary detection. The main contribution is a probabilistic detection framework defined on spatio-temporal lattices, which en...
Mehmet Emre Sargin, Luca Bertelli, Bangalore S. Ma...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
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...
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
We present a novel action recognition method which is based on combining the effective description properties of Local Binary Patterns with the appearance invariance and adaptabil...