Compacted Dither Pattern Codes Over MPEG-7 Dominant Colour Descriptor In Video Visual Depiction

Abstract

Reduction of feature space of visual descriptors has become important due to the ‘curse of dimensionality’ problem. This paper reports the efficiency and effectiveness of the Compacted Dither Pattern Code (CDPC) combined with the Bhattacharyya classifier over MPEG-7 Dominant Colour Descriptor (DCD). Both the CDPC and DCD syntactic features use a compact feature space for colour representation. The algorithmic comparison between the two is presented in this paper, and demonstrates that there are several competitive advantages of CDPC in feature extraction and classification stages when compared to MPEG-7 DCD. The embedded texel properties, spatial colour arrangements, high compactness, and robust feature representation of CDPC have proven its effectiveness in our experimental study. Visual description experiments were conducted for ten irregular shapes-based visual concepts in videos with three setups namely CDPC with Bhattacharyya classifier, DCD without spatial coherency and DCD with spatial coherency. The visual descriptions were performed with the TRECVID 2007 development key frame dataset. The experimental results are presented in terms of three common performance measures. The results show that CDPC with Bhattacharyya classifier provides a good generalised performance for irregular shapes-based visual description as compared to the other experimental setups.