Shot classification for action movies based on motion characteristics
In this paper, we propose a shot classification method for action movies. Considering that motion characteristic is very important for semantic movie analysis, and it contains abundant information in action movies, the structure tensor analysis is used for feature extraction due to its capability of representing both spatial and temporal characteristics of a shot. Firstly, the movie shots with known labels are decomposed into a set of overlapped fixed-length segments and their structure tensor histogram are computed. The labels of segments are identical to the shots they belong to. Then Adaboost is used to train the semantic classifier with these structure tensor histogram sets. In testing procedure, the unknown shot are decomposed in the same way, and feature vector of each segment is extracted and classified by the classifier. Finally, the label of the shot is generalized by the segment label voting scheme. Experimental results show that this scheme could effectively deal with multiple motion patterns within shots and promising results are achieved.