Copy detection of 3D videos

We present a novel content based copy detection system for 3D videos. The system creates compact and robust depth and visual signatures from 3D videos. The system returns a score, using both spatial and temporal characteristics of videos, indicating whether a given query video matches any video in a reference video database, and in case of matching, which portion of the reference video matches the query video. Our analysis shows that the system is efficient, both computationally and storage wise. The system can be used, for example, by video content owners, video hosting sites, and third-party companies to find illegally copied 3D videos. We implemented Spider, a complete realization of the proposed system, and conducted rigorous experiments on it. Our experimental results show that the proposed system can achieve high accuracy in terms of precision and recall even if copied 3D videos are subjected to several modifications at the same time. For example, the proposed system yields 100% precision and recall when copied videos are parts of original videos, and more than 90% precision and recall when copied videos are subjected to different individualmodifications such as cropping, scaling, and blurring.