Foreground object detection from videos containing complex background
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Hidden Markov Models for Optical Flow Analysis in Crowds
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Deriving implicit indoor scene structure with path analysis
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
| Hi-index | 0.00 |
We present a tool that automatically detects abnormal situations in crowded scenes in real time. The followed approach analyzes the general motion aspect, instead of tracking subjects one by one, by detecting abnormal optical flow patterns of tracked KLT points. The number of tracked points is reduced by using a learned mask. We define a measure that describes the situation abnormality based on crowd density, direction variance and distribution, mean velocity and sometimes trajectory matching. To demonstrate the interest of this approach, we present the results on the detection of collapsing events in real videos of airport escalator exits.