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CVPR
2010
IEEE
13 years 5 months ago
Scene understanding by statistical modeling of motion patterns
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of pattern...
Imran Saleemi, Lance Hartung, Mubarak Shah
CVPR
2010
IEEE
14 years 1 months ago
Tracking with Local Spatio-Temporal Motion Patterns in Extremely Crowded Scenes
Tracking individuals in extremely crowded scenes is a challenging task, primarily due to the motion and appearance variability produced by the large number of people within the sc...
Louis Kratz, Ko Nishino
CVPR
2009
IEEE
15 years 15 days ago
Anomaly Detection in Extremely Crowded Scenes using Spatio-Temporal Motion Pattern Models
Extremely crowded scenes present unique challenges to video analysis that cannot be addressed with conventional approaches. We present a novel statistical framework for modeling...
Louis Kratz (Drexel University), Ko Nishino (Drexe...
CVPR
2010
IEEE
14 years 1 months ago
Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes
A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique ut...
Shandong Wu, Brian E. Moore, and Mubarak Shah
ICPR
2008
IEEE
13 years 11 months ago
Evaluation of clustering methods for finding dominant optical flow fields in crowded scenes
Video footage of real crowded scenes still poses severe challenges for automated surveillance. This paper evaluates clustering methods for finding independent dominant motion fi...
Günther Eibl, Norbert Brändle