신경망을 이용한 효율적인 비디오 컨텐츠 분류 방법

Abstract

This paper proposes a method to classify different video contents using features of digital video. Classified video types are the news, drama, show, sports and talk program. Features such as intra-coded macroblock number & motion vector in P--picture in MPEG domain are used. The frame difference of YCbCr is also employed as a measure of classification. We detect the occurrences of cuts in a video for a measure of classification. Finally, back-propagation neural-network of 3 layers is used to classify vicep contents.