Call For Paper Volume:4 Issue:10 Oct'2017 |

SIFT Based Video Copy Detection

Publication Date : 10/07/2015

Author(s) :

Swapnil S.Kharat , Mayur Ingale , Lalit Shevkani , Rakeshkumar Yadav.

Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India

Abstract :

Due to advances in multimedia compression technology and growth of internet, digital videos are widely used. These videos can be found on public video web servers, TV channels and video blogs. Hence there is need for automated procedures to protect the owner of video against unauthorized use of their video content, preventing copyright violations. The video can be altered by various transformations. This paper presents video copy detection method using SIFT (Scale Invariant Feature Transform) descriptors. To reduce the computational complexity of SIFT; first we used the dual-threshold method to segment the videos into segments and extract key-frames from each segment. SIFT features are extracted from the key-frames of the segments. Then a nearest neighbor method is used to match two video frames with SIFT point set descriptors. We have also compared the performance of SIFT descriptor with Trajkovic detector for various types of transformations. The distinguishing feature of our method is that it is capable of detecting the most difficult transformation: Picture-in-Picture. We have also tested our system for four other types of transformations as well

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