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...
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...
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...
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 ...
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...