Abstract:
The high usage of the Internet, in particular videosharing and social networking websites, have led to enormous amount of video data recently, raising demand on effective...Show MoreMetadata
Abstract:
The high usage of the Internet, in particular videosharing and social networking websites, have led to enormous amount of video data recently, raising demand on effective and efficient content-based near-duplicate video detection approaches. In this paper, we propose to efficiently search for near-duplicate videos via the utilization of efficient approximation techniques of the well-known effective similarity measure Earth Mover's Distance (EMD). To this end, we model keyframes by flexible feature representations which are then exploited in a filter-and-refine architecture to alleviate the query processing time. The experiments on real data indicate high efficiency guaranteeing reduced number of EMD computations, which contributes to the near-duplicate detection in video datasets.
Date of Conference: 10-12 June 2015
Date Added to IEEE Xplore: 13 July 2015
Electronic ISBN:978-1-4673-6870-4