Video shot boundary detection using RBFNN minimizing the L-GEM

Shot boundary detection (SBD) is the key step of key frame extraction for Content-Based Video Retrieval (CBVR). In this paper, we propose a shot boundary detection method by Radial Basis Function Neural Network (RBFNN) trained via a minimization of the Localized Generalization Error (L-GEM). Frame differences are classified as either boundary or non-boundary by the RBFNN. The statistical features of DC image extracted from each frame are used as the input features describing the frame difference. The proposed SBD method is compared with an existing method using News videos. Experimental results show that the proposed method is effective.