Title :
Statistical modeling and analysis of content identification
Author_Institution :
Beckman Inst., Coord. Sci. Lab., ECE Dept., Univ. of Illinois, Urbana, IL, USA
fDate :
Jan. 31 2010-Feb. 5 2010
Abstract :
A number of hash-based algorithms for audio and video identification (ID) have been studied in recent literature, and some have been deployed as mobile phone applications and on file sharing sites. A fundamental question is what is the relationship between database size, hash length, and robustness, that any reliable content ID system should satisfy. This paper presents some answers under a simple statistical model for the signals of interest.
Keywords :
content-based retrieval; cryptography; fingerprint identification; statistical analysis; audio identification; content ID system; content identification; database size; hash length; hash-based algorithm; robustness; statistical modeling; video identification; Content based retrieval; Databases; Decoding; Fingerprint recognition; Information retrieval; Peer to peer computing; Probes; Robustness; Signal processing algorithms; Video sharing; Content identification; audio; capacity; decoding; error exponents; fingerprinting; hashing; strong converse; video;
Conference_Titel :
Information Theory and Applications Workshop (ITA), 2010
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7012-9
Electronic_ISBN :
978-1-4244-7014-3
DOI :
10.1109/ITA.2010.5454105
