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Content Identification Based on digital fingerprint : what can be done if ML decoding fails?

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Published in 2010 IEEE International Workshop on Multimedia Signal Processing (MMSP). Saint-Malo (France) - 4-6 Oct. 2010 - Institute of Electrical and Electronics Engineers ( IEEE ). 2010, p. 64-68
Abstract In this paper, the performance of the content identification based on digital fingerprinting and order statistic list decoding is analyzed by evaluating the probabilities of correct identification, false acceptance and the probability mass function of queried binary fingerprint position on the list of candidates. The particular attention is dedicated to the cases when traditional maximum likelihood decoder fails to produce the reliable content identification. The maximum likelihood decoding is shown to be a particular case of order statistic list decoding for the list size equals 1. We demonstrate the efficiency of the proposed content identification system performance by investigating the probability mass function behavior and imposing the constraint on the cardinality of list size.
Keywords fingerprint identificationmaximum likelihood decodingprobability
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Research groups Computer Vision and Multimedia Laboratory
Stochastic Information Processing Group
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FARHADZADEH, Farzad, VOLOSHYNOVSKYY, Svyatoslav, KOVAL, Oleksiy. Content Identification Based on digital fingerprint : what can be done if ML decoding fails?. In: 2010 IEEE International Workshop on Multimedia Signal Processing (MMSP). Saint-Malo (France). [s.l.] : Institute of Electrical and Electronics Engineers ( IEEE ), 2010. p. 64-68. doi: 10.1109/MMSP.2010.5661995 https://archive-ouverte.unige.ch/unige:47634

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Deposited on : 2015-03-06

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