Video Classification and Shot Detection for Video Retrieval Applications
M. Kalaiselvi Geetha, S. Palanivel · International Journal of Computational Intelligence Systems · 2009
Appropriate organization of video databases is essential for pertinent indexing and retrieval of visual information.This paper proposes a new feature called Block Intensity Comparison Code (BICC) for video classification and an unsupervised shot change detection algorithm to detect the shot changes in a video stream using autoassociative neural network (AANN) which makes retrieval problems much simpler.BICC represents the average block intensity difference between blocks of a frame.A novel AANN misclustering rate (AMR) algorithm is used to detect the shot transitions.The experiments demonstrate the effectiveness of the proposed methods.