Time-space acoustical feature for fast video copy detection

We propose a new time-space acoustical feature for fast video copy detection to search a video segment for a number of video streams to find illegal video copies on Internet video site and so on. We extract a small number of feature vectors from acoustically peculiar points that express the point of local maximum/minimum in the time sequence of acoustical power envelopes in video data. The relative values of the feature points are extracted, so called time-space acoustical feature, because the volume in the video stream differs in different recording environments. The features can be obtained quickly compared with representative features such as MFCC, and they require a short processing time for matching because the number and the dimension of each feature vector are both small. The accuracy and the computation time of the proposed method is evaluated using recorded TV movie programs for input data, and a 30 sec. −3 min. segment in DVD for reference data, assuming a copyright holder of a movie searches the illegal copies for video streams. We could confirm that the proposed method completed all processes within the computation time of the former feature extraction with 93.2% of F-measure in 3 minutes video segment detection.