Scene cut detection using the colored pattern appearance model

In this paper, we propose to use the colored pattern appearance model (CPAM) as a content representation for video scene break detection. This model represents a scene by means of global statistics of the local visual appearance, and was originally motivated by studies in human color vision. The performance of this method is compared to several histogram-based approaches. An adaptive thresholding technique, namely entropic thresholding, is applied to determine the respective optimal threshold values for each of the approaches. In the experiments, the two video sequences in the MPEG-7 content set are used to evaluate the performances of the CPAM and the histogram-based methods. Experimental results show that our proposed model outperforms other histogram-based approaches in scene break detection.