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Published in:
2014 | OriginalPaper | Chapter
Vehicle Recognition for Surveillance Video Using Sparse Coding
Authors : Shirong Zeng, Xin Niu, Yong Dou
Published in: Pattern Recognition
Publisher: Springer Berlin Heidelberg
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This paper presents a vehicle recognition approach for a real transportation surveillance system using sparse coding. Comparison between sparse coding and conventional histogram of orientation gradient (HOG) has been studied. The results showed that the sparse coding learned feature is better than HOG feature in such vehicle recognition application. Experiments indicated that overlapping spatial pooling over the learned sparse codes can improve accuracy in a great deal.