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ICCV
2009
IEEE
1190views Computer Vision» more  ICCV 2009»
16 years 2 months 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
14 years 4 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
15 years 11 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
15 years 11 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
15 years 11 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