Video Event Detection Using Auto-Associative Neural Network And Incremental Svm Models
2015 15TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA)(2015)
摘要
In this paper a new approach to video event detection is presented. This approach is based on HOG/HOF features optimized by an auto-associative neural network models for feature reduction and an incremental SVM model for event classification. This auto-associative neural network models are frequently used to reduce the size of feature vectors. In our approach, each event is modeled by a set of states, and each state is represented by a learning model containing a positive class (event) and a negative class (non-event). Experiments on real video sequences have shown encouraging results.
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关键词
Event detection,HOG/HOF features,autoassociative memory,modeling
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