Unsupervised abnormal crowd activity detection in surveillance systems
Łukasz Kamiński, Paweł Gardziński, Krzysztof Kowalak, Sławomir Maćkowiak · 2016
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.