Fast Video Retrieval via the Statistics of Motion

[[abstract]]Due to the popularity of the Internet and the powerful computing capability of computers, efficient processing/retrieval of multimedia data has become an important issue. In this paper, we propose a fast video retrieval algorithm that bases its search core on the statistics of object motion. The algorithm starts with extracting object motions from a shot and then transform/quantize them into the form of probability distributions. By choosing the shot that has the largest entropy value among the constituent shots of an unknown query video clip, we execute the first stage video search.By comparing two shots with different lengths, their corresponding motion probability distributions are compared by a discrete Bhattacharyya distance which is designed to measure the similarity between any two distribution functions. In the second stage, we add an adjacent shot(either preceding or subsequent) to perform a finer comparison. Experimental results demonstrate that our fast video retrieval algorithm is powerful in terms of accuracy and efficiency.[[fileno]]2030144030026[[department]]電機工程學