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ICCV
2009
IEEE
1190views Computer Vision» more  ICCV 2009»
15 years 20 days ago
You'll never walk alone: modeling social behavior for multi-target tracking
Object tracking typically relies on a dynamic model to predict the object’s location from its past trajectory. In crowded scenarios a strong dynamic model is particularly impo...
S. Pellegrini, A. Ess, K. Schindler, L. van Gool
ACCV
2010
Springer
13 years 2 months ago
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos
Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
CVPR
2007
IEEE
14 years 9 months ago
Precise Registration of 3D Models To Images by Swarming Particles
The precise alignment of a 3D model to 2D sensor images to recover the pose of an object in a scene is an important topic in computer vision. In this work, we outline a registrati...
Joerg Liebelt, Klaus Schertler
CVPR
2007
IEEE
14 years 9 months ago
Optimizing Distribution-based Matching by Random Subsampling
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Alex Po Leung, Shaogang Gong
ICCV
2001
IEEE
14 years 9 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black