CASIA OpenIR  > 09年以前成果
Learning activity patterns using fuzzy self-organizing neural network
Hu, WM; Xie, D; Tan, TN; Maybank, S
AbstractActivity understanding in visual surveillance has attracted much attention in recent years. In this paper, we present a new method for learning patterns of object activities in image sequences for anomaly detection and activity prediction. The activity patterns are constructed using unsupervised learning of motion trajectories and object features. Based on the learned activity patterns, anomaly detection and activity prediction can be achieved. Unlike existing neural network based methods, our method uses a whole trajectory as an input to the network. This makes the network structure much simpler. Furthermore, the fuzzy set theory based method and the batch learning method are introduced into the network learning process, and make the learning process much more efficient. Two sets of data acquired, respectively, from a model scene and a campus scene are both used to test the proposed algorithms. Experimental results show that the fuzzy self-organizing neural network (fuzzy SOM) is much more efficient than the Kohonen self-organizing feature map (SOFM) and vector quantization in both speed and accuracy, and the anomaly detection and activity prediction algorithms have encouraging performances.
KeywordActivity Prediction Anomaly Detection Fuzzy Som Learning Activity Patterns
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000221578100029
Citation statistics
Cited Times:84[WOS]   [WOS Record]     [Related Records in WOS]
Document Type专利
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100080, Peoples R China
2.Univ London Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HX, England
Recommended Citation
GB/T 7714
Hu, WM,Xie, D,Tan, TN,et al. Learning activity patterns using fuzzy self-organizing neural network[P]. 2004-06-01.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Hu, WM]'s Articles
[Xie, D]'s Articles
[Tan, TN]'s Articles
Baidu academic
Similar articles in Baidu academic
[Hu, WM]'s Articles
[Xie, D]'s Articles
[Tan, TN]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Hu, WM]'s Articles
[Xie, D]'s Articles
[Tan, TN]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.