COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Online Choice of Active Learning Algorithms
The Journal of Machine Learning Research
Video Behavior Profiling for Anomaly Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active learning for object classification: from exploration to exploitation
Data Mining and Knowledge Discovery
Gaussian Processes for Object Categorization
International Journal of Computer Vision
Abnormal event detection via multi-instance dictionary learning
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Multicamera video summarization and anomaly detection from activity motifs
ACM Transactions on Sensor Networks (TOSN)
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We present a new active learning approach to incorporate human feedback for on-line unusual event detection. In contrast to most existing unsupervised methods that perform passive mining for unusual events, our approach automatically requests supervision for critical points to resolve ambiguities of interest, leading to more robust and accurate detection on subtle unusual events. The active learning strategy is formulated as a stream-based solution, i.e. it makes decision on-the-fly on whether to query for labels. It adaptively combines multiple active learning criteria to achieve (i) quick discovery of unknown event classes and (ii) refinement of classification boundary. Experimental results on busy public space videos show that with minimal human supervision, our approach outperforms existing supervised and unsupervised learning strategies in identifying unusual events. In addition, better performance is achieved by using adaptive multi-criteria approach compared to existing single criterion and multi-criteria active learning strategies.