Abstract
This paper presents comparative evaluation of a robust frame-level descriptor for video identification, called a Video Signature, which was previously developed by the authors and was accepted as part of a new ISO/IEC standard “MPEG-7 Video Signature Tools”. The Video Signature is designed for video copy detection from a large-scale database, with robustness to various modifications, including caption overlay, camera capturing, compression, and color changes, working at extremely low false positive rate. It represents intensity differences between various sub-regions in a frame, which are configured at variety of scales, shapes, and locations in the frame, to provide robustness and uniqueness to the descriptor. The intensity differences are quantized into ternary values, resulting in a compact representation of 76 bytes per frame. Furthermore, a confidence value is calculated for each frame, which is used in the matching process to significantly reduce false positives. An experiment to identify videos under nine types of modifications was carried out to compare the performance of the Video Signature to that of the conventional color-based and spatial visual features. The results show that the Video Signatures improves the detection rate for all modification types compared with the conventional features, in particular significant increase by 38.8% for caption overlay and 61.8% for camera capturing have been achieved. We also present a system for structuring a large-scale video database using the Video Signature, developed for efficient management of video contents. The details of the system are explained and its feasibility as an application is shown.
