Video Anomaly Detection Based on Hierarchical Clustering-Reference-Cited by-同舟云学术

Video Anomaly Detection Based on Hierarchical Clustering

Published:2019 Issue: Volume: Page:547-559
ISSN:0302-9743
Container-title:Human Centered Computing
language:
Short-container-title:

Author:

Zhao Chunyue,Li Beichen,Wang Qing,Wang Zhipeng

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-15127-0_55

Reference26 articles.

1. Jiang, F., Wu, Y., Katsaggelos, A.K.: A dynamic hierarchical clustering method for trajectory-based unusual video event detection. IEEE Trans. Image Process. 18(4), 907–13 (2009). Publication of the IEEE Signal Processing Society

2. Ren, H., Liu, W., Olsen, S.I., et al.: Unsupervised behavior-specific dictionary learning for abnormal event detection. IEEE Trans. Signal Process. 17(2), 99–111 (2015)

3. Yuan, Y., Feng, Y., Lu, X.: Structured dictionary learning for abnormal event detection in crowded scenes. Pattern Recogn. 62(4), 129–138 (2018)

4. Zhang, Z., Mei, X., Xiao, B.: Abnormal event detection via compact low-rank sparse learning. IEEE Intell. Syst. 31(2), 29–36 (2016)

5. Lu, C., Shi, J., Jia, J.: Abnormal event detection at 150 FPS in MATLAB. In: IEEE International Conference on Computer Vision, pp. 2720–2727. IEEE (2014)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unsupervised adversarial domain adaptation abnormal sound detection for machine condition monitoring under domain shift conditions;2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC);2021-10-29