Video Classification and Shot Detection for Video Retrieval Applications
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.
video classification block intensity comparison code misclustering rate shot transition video indexing