Abstract

This paper proposes a method for identifying the video that retains the most information from its parent video. Since the parent video is often unavailable, the proposed method estimates its content through the collaborative use of the available video signals that are edited copies of the parent video. By reducing the difference between the video signals of the edited videos, the proposed method then enables the use of conventional no-reference video quality assessment algorithms. Since editing a video requires recompressing it, and since quality assessment algorithms can detect signs of recompression, the proposed method can identify the edited video that retains the most information from the parent video. The effectiveness of the proposed method is verified by subjective experiments over artifical and real-world data sets that include a total of over 400 videos.

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