TV Commercial Categorization Based on Sparse Visual Bag of Words

Abstract

Automatic TV commercial categorization is the key component of a smart commercial content analysis and understanding system. In this paper, we focus our research on commercial categorization by mining the temporal-spatial context of TV commercial. To boost the discrimination ability of the traditional VBoW in commercial categorization, a more flexible representation, i.e. sparse coding based VBoW (sVBoW), is presented to describe the co-occurrence of semantic units in different kinds of commercials. Meanwhile, both the temporal and spatial cues are fully exploited to reflect the context characteristics of TV commercial. The promising experimental results show the effectiveness of the proposed scheme on commercial categorization.