Statistical Modeling and Analysis of Content Identification

被引：0
|
作者：
Moulin, Pierre [1 ]
机构：
[1] Univ Illinois, ECE Dept, Beckman Inst, Coord Sci Lab, 405 N Mathews Ave, Chicago, IL 61801 USA
来源：
2010 INFORMATION THEORY AND APPLICATIONS WORKSHOP (ITA) | 2010年
关键词：
Content identification; audio; video; hashing; fingerprinting; decoding; error exponents; capacity; strong converse; ERASURE; LIST;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：329 / 333
页数：5
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