Video sequence boundary detection using neural gas networks

Video sequence boundary detection is an important first step in the construction of efficient and user-friendly video archives, In this paper, we propose to employ growing neural gas (GNG) networks [7] to detect the shot boundaries, as the neural networks are capable of learning the characteristics of various shots and clustering them accordingly. We represent the image frames by 6-bit color-coded histograms. We make use of the chi-square distances between histograms of neighboring frames as the primary features to train the GNG and to detect the shot boundaries. Experimental results presented in this paper demonstrate the reliable performance of our proposed approach on real video sequences.