scholarly journals Video Copy Detection Using Spatio-Temporal CNN Features

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 100658-100665 ◽  
Author(s):  
Zhili Zhou ◽  
Jingcheng Chen ◽  
Ching-Nung Yang ◽  
Xingming Sun
2013 ◽  
Vol 347-350 ◽  
pp. 3653-3661
Author(s):  
Wei Bao ◽  
Li Xin Ji ◽  
Shi Lin Gao ◽  
Xing Li ◽  
Li Xiong Liu

A video copy detection method based on fusion of spatio-temporal features is proposed in this paper. Firstly, trajectories are built and lens boundaries are detected by SURF features analyzing, then normalized histogram is used to describe spatio-temporal behavior of trajectories, the bag of visual words is constructed by trajectories behavior clustering, word frequency vectors and SURF features with behavior labels are extracted to express spatio-temporal content of lens, finally, duplicates are detected efficiently based on grade-match. The experimental results show the performance of this method is improved greatly compared with other similar methods.


2010 ◽  
Vol 12 (4) ◽  
pp. 257-266 ◽  
Author(s):  
Matthijs Douze ◽  
Hervé Jegou ◽  
Cordelia Schmid

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