Unsupervised Abnormal Crowd Activity Detection in Surveillance Systems
[ 1 ] Wydział Elektroniki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Katedra Telekomunikacji Multimedialnej i Mikroelektroniki, Wydział Elektroniki i Telekomunikacji, Politechnika Poznańska | [ D ] phd student | [ P ] employee
2016
paper
english
- particle filter
- unsupervised anomaly detection
- UMN
EN We propose an unsupervised method for abnormal crowd activity detection in surveillance systems. Proposed solution is using MPEG-7 Motion Activity descriptors and Particle Filter algorithm for classification. The experiments were performed on UMN dataset sequences. The detection results are comparable to results obtained by supervised methods.
65 - 68
WoS (15)