Skip to Main Content
This paper presents applications for dealing with videos on the Web, using an efficient technique for video copy detection in large archives. Managing videos on the Web is the source of two exciting challenges: the respect of the copyright and the linkage of multiple videos. We present a technique called ViCopT for video copy tracking which is based on labels of behavior of local descriptors computed along video. The results obtained on large amount of data (270 hours of videos from the Internet) are very promising, even with a large video database (700 hours): ViCopT displays excellent robustness to various severe signal transformations, making it able to identify copies accurately from highly similar videos, as well as to link similar videos, in order to reduce redundancy or to gather the metadata associated. Finally, we also show that ViCopT goes further by detecting segments having the same background, with the aim of linking videos of the same category, like forecast weather programs or particular TV shows.