Content-Based Affective Intensity Recognition Algorithm Using Unascertained Measure

Abstract

Affective content recognition is an unsolved technical problem in intricate video retrieval and high-level applications. In this paper , a few video retrieval problems are studied at the view of affective intensity recognition. A novel algorithm about video scene affective intensity recognition, which is based on the unascertained measure, is proposed. The algorithm consists of two parts. Firstly, the sub-module of video affective intensity features extraction introduces the affective intensity feature extraction sub-models of the shots correlation coefficient（SCC） and the duration ratio of the shots（DROS）. Secondly, the sub-module of affective intensity determination includes the unascertained intensity measure matrix of video scene and video affective intensity type recognition sub-model. The experimental results show that the proposed algorithm is feasible and achieves more than 70 percent accuracy.