Paper Title:
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.

  Info
Periodical
Edited by
Yuanzhi Wang
Pages
476-481
DOI
10.4028/www.scientific.net/AMM.39.476
Citation
L. L. Yan, X. M. Wen, W. Zheng, L. Zhang, "Content-Based Affective Intensity Recognition Algorithm Using Unascertained Measure", Applied Mechanics and Materials, Vol. 39, pp. 476-481, 2011
Online since
November 2010
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