Detecting Irregularities in Images and in Video
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
IEEE Transactions on Signal Processing
Motion-based unusual event detection in human crowds
Journal of Visual Communication and Image Representation
Anomalous video event detection using spatiotemporal context
Computer Vision and Image Understanding
Detecting anomalies in people's trajectories using spectral graph analysis
Computer Vision and Image Understanding
Multi-scale and real-time non-parametric approach for anomaly detection and localization
Computer Vision and Image Understanding
Hi-index | 0.00 |
Many works have been proposed on detecting individual anomalies in crowd scenes, i.e., human behaviors anomalous with respect to the rest of the behaviors. In this paper, we introduce a new concept of contextual anomaly into the field of crowd analysis, i.e., the behaviors themselves are normal but they are anomalous in a specific context. Our system follows an unsupervised approach. It automatically discovers important contextual information from the crowd video and detects the blobs corresponding to contextually anomalous behaviors. Our experiments show that the approach works well in detecting contextual anomalies from crowd video with different motion contexts.