Cinematography sequences tracking by means of fingerprinting techniques
Video fingerprints are short features extracted from a video sequence in order to uniquely identify its visual content and its replicas. By advancing a new robust fingerprinting method, the present paper takes the challenge of designing an enabler for the use of Internet as a distribution tool in cinematography. In this respect, a 2D-DWT-based robust video fingerprinting method is designed so as to address two use cases, namely the retrieval of video content from a database and the tracking of in-theater camcorder recorded video content. A set of largest absolute value wavelet coefficients is considered as the fingerprint and a repeated statistical test is used as the matching procedure. The video dataset consists of two corpora, one for each use case. The first corpus regroups 3h of heterogeneous original content (organized under the framework of the HD3D-IIO French national project) and of its attacked versions (a total of 21h of video content). The second corpus consists of 3h of heterogeneous content (i.e., HD3D-IIO corpus) and of 1h of live camcorder recorded video content (a total of 4h of video content). The inner 2D-DWT properties with respect to content-preserving attacks (such as linear filtering, sharpening, geometric, conversion to grayscale, small rotations, contrast changes, brightness changes, and live camcorder recording) ensure the following results: in the first use case, the probability of false alarm and missed detection are lower than 0.0005, precision and recall are higher than 0.97; in the second use case, the probability of false alarm is 0.00009, the probability of missed detection is lower than 0.0036, precision and recall are equal to 0.72.
uniqueness robustness robust video fingerprinting live camcorder recording dwt