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CVPR
2009
IEEE
14 years 12 months 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...
ICASSP
2011
IEEE
12 years 8 months ago
Abnormal motion detection in crowded scenes using local spatio-temporal analysis
We present a motion classification approach to detect movements of interest (abnormal motion) based on local feature modeling within spatio-temporal detectors. The modeling is pe...
Fahad Daniyal, Andrea Cavallaro
CVPR
2010
IEEE
14 years 23 days 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
ICPR
2008
IEEE
14 years 6 months ago
Real-time crowd motion analysis
Video-surveillance systems are becoming more and more autonomous in the detection and the reporting of abnormal events. In this context, this paper presents an approach to detect ...
Chabane Djeraba, Nacim Ihaddadene
ICPR
2010
IEEE
13 years 2 months ago
Online Learning with Self-Organizing Maps for Anomaly Detection in Crowd Scenes
Detecting abnormal behaviors in crowd scenes is quite important for public security and has been paid more and more attentions. Most previous methods use offline trained model to p...
Jie Feng, Chao Zhang, Pengwei Hao