Two algorithms for nearest-neighbor search in high dimensions
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Locally lifting the curse of dimensionality for nearest neighbor search (extended abstract)
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Feature Extraction and a Database Strategy for Video Fingerprinting
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Content-Based Identification of Audio Titles on the Internet
WEDELMUSIC '01 Proceedings of the First International Conference on WEB Delivering of Music (WEDELMUSIC'01)
On the automated recognition of seriously distorted musicalrecordings
IEEE Transactions on Signal Processing
Digital Watermarking and Steganography
Digital Watermarking and Steganography
Quantum hashing for multimedia
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Thick boundaries in binary space and their influence on nearest-neighbor search
Pattern Recognition Letters
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Audio fingerprinting is an emerging research field in which a song must be recognized by matching an extracted "fingerprint" to a database of known fingerprints. Audio fingerprinting must solve the two key problems of representation and search. In this paper, we are given an 8192-bit binary representation of each five second interval of a song and therefore focus our attention on the problem of high-dimensional nearest neighbor search. High dimensional nearest neighbor search is known to suffer from the curse of dimensionality, i.e. as the dimension increases, the computational or memory costs increase exponentially. However, recently, there has been significant work on efficient, approximate, search algorithms. We build on this work and describe preliminary results of a probabilistic search algorithm. We describe the data structures and search algorithm used and then present experimental results for a database of 1,000 songs containing 12,217,111 fingerprints.