Event recognition based on bag of local space-time interest points' features
Chuan-Min Zhai, Yi-Lan Guo, Ji‐Xiang Du · 2011
This paper proposes a novel method based on bag of local space-time interest points' features to recognize and retrieval complex events in real movies. In this method, an individual video sequence is represented as a bag of local space-time features then we integrate such bag-of-feature with SVM for recognition events. Local space-time features are introduced to capture the local events in video and can be adapted to size and velocity of the pattern of the event. To evaluate effectiveness of this method, this paper uses the public Hollywood dataset, in this dataset the shot sequences has collected from 32 different Hollywood movies and it includes 8 event classes. The presented result justify the proposed method explicitly improve the average accuracy and average precision compared to other relative approaches.