3D content fingerprinting
Fingerprint is a set of features that uniquely characterizes a video. The aim of content fingerprinting is to determine the duplicate videos over the Internet. In this paper, a method for content fingerprinting of Depth-Image-Based-Rendering (DIBR) 3D videos is proposed. The proposed method is two pronged approach: (i) histogram based global fingerprint and (ii) keypoint based local fingerprint. Though global fingerprint is fast and robust towards DIBR 3D pre-processing, it is not robust against severe distortions such as change in brightness. To make the proposed method robust against such severe distortions, we have complemented the global fingerprint with widely used keypoint based local fingerprint. Experimental results show that the proposed two pass method as robust as keypoint based local fingerprinting method. Additionally, the proposed method improves the video matching time of keypoint based local fingerprint method by 60% to 100%.