%0 Conference Proceedings %F dvmmPub89 %A Sundaram, Hari %A Chang, Shih-Fu %T Efficient Video Sequence Retrieval in Large Repositories %B IS&T/SPIE Symposium on Electronic Imaging: Science and Technology (EI'99) - Visual Communications and Image Processing (VCIP) %C San Jose, CA %X This paper presents algorithms to deal with problems associated with indexing high-dimensional feature vectors that characterize video data. Indexing high dimensional vectors is well known to be computationally expensive. Our solution is to optimally split the high dimensional vector into a few low dimensional feature vectors and querying the system for each feature vector. This involves solving an important sub-problem: developing a model for retrieval that enables us to query the system efficiently. Once we formulate the retrieval problem in terms of a retrieval model, we present an optimality criterion to maximize the number of results using this model. The criterion is based on a novel idea of using the underlying probability distribution of the feature vectors. A branch-and-prune strategy optimized per each query, is developed. This uses the set of features derived from the optimality criterion. Our results show that the algorithm performs well, giving a speedup of a factor of 25 with respect to a linear search while retaining the same level of recall %U http://www.ee.columbia.edu/dvmm/publications/99/ei99.pdf %8 January %D 1999