Robust content-based video copy identification in a large reference database

Abstract

This paper proposes a novel scheme for video content-based copy identification dedicated to TV broadcast with a reference video database exceeding 1000 hours of video. It enables the monitoring of a TV channel in soft real-time with a good tolerance to strong transformations that one can meet in any TV post-production process like: clipping, cropping, shifting, resizing, objects encrusting or color variations. Contrary to most of the existing schemes, the recognition is not based on global features but on local features extracted around interest points. This allows the selection and the localization of fully discriminant local patterns which can be compared according to a distance measure. Retrieval is performed using an efficient approximate Nearest Neighbors search and a final decision based on several matches cumulated in time. © Springer-Verlag Berlin Heidelberg 2003.