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ECCV
2008
Springer
14 years 10 months ago
Learning Spatial Context: Using Stuff to Find Things
The sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the...
Geremy Heitz, Daphne Koller
ICASSP
2011
IEEE
13 years 17 days ago
Efficient block-division model for robust multiple object tracking
Tracking multiple objects under occlusion is one of the most challenging issues in computer vision. Occlusion results in mistaken match when finding the most similar candidate. A...
Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weimin...
ICCV
2003
IEEE
14 years 2 months ago
Tracking Across Multiple Cameras With Disjoint Views
Conventional tracking approaches assume proximity in space, time and appearance of objects in successive observations. However, observations of objects are often widely separated ...
Omar Javed, Zeeshan Rasheed, Khurram Shafique, Mub...
ECCV
2008
Springer
14 years 10 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
ICCV
2009
IEEE
15 years 1 months ago
Correlated Probabilistic Trajectories for Pedestrian Motion Detection
This paper introduces an algorithm for detecting walking motion using point trajectories in video sequences. Given a number of point trajectories, we identify those which are sp...
Frank Perbet, Atsuto Maki, Bjorn Stenger