The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
The Journal of Machine Learning Research
Non-negative Matrix Factorization with Sparseness Constraints
The Journal of Machine Learning Research
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
The Journal of Machine Learning Research
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Unusual Event Detection using Multiple Fixed-Location Monitors
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
A streakline representation of flow in crowded scenes
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Sparse reconstruction cost for abnormal event detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Online detection of unusual events in videos via dynamic sparse coding
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Abnormal detection using interaction energy potentials
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Non-negative matrix factorization as a feature selection tool for maximum margin classifiers
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Boosted Exemplar Learning for Action Recognition and Annotation
IEEE Transactions on Circuits and Systems for Video Technology
Video anomaly detection based on local statistical aggregates
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Video parsing for abnormality detection
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Exploiting sparse representations for robust analysis of noisy complex video scenes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Robust Visual Tracking via Structured Multi-Task Sparse Learning
International Journal of Computer Vision
Supervised Dictionary Learning via Non-negative Matrix Factorization for Classification
ICMLA '12 Proceedings of the 2012 11th International Conference on Machine Learning and Applications - Volume 01
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In crowded scenes, the extracted low-level features, such as optical flow or spatio-temporal interest point, are inevitably noisy and uncertainty. In this paper, we propose a fully unsupervised non-negative sparse coding based approach for abnormality event detection in crowded scenes, which is specifically tailored to cope with feature noisy and uncertainty. The abnormality of query sample is decided by the sparse reconstruction cost from an atomically learned event dictionary, which forms a sparse coding bases. In our algorithm, we formulate the task of dictionary learning as a non-negative matrix factorization (NMF) problem with a sparsity constraint. We take the robust Earth Mover's Distance (EMD), instead of traditional Euclidean distance, as distance metric reconstruction cost function. To reduce the computation complexity of EMD, an approximate EMD, namely wavelet EMD, is introduced and well combined into our approach, without losing performance. In addition, the combination of wavelet EMD with our approach guarantees the convexity of optimization in dictionary learning. To handle both local abnormality detection (LAD) and global abnormality detection, we adopt two different types of spatio-temporal basis. Experiments conducted on four public available datasets demonstrate the promising performance of our work against the state-of-the-art methods.