DocumentCode :
1414154
Title :
A Probabilistic Approach to Pattern Matching in the Continuous Domain
Author :
Keren, Daniel ; Werman, Michael ; Feinberg, Joshua
Author_Institution :
University of Haifa, Haifa
Volume :
34
Issue :
10
fYear :
2012
Firstpage :
1873
Lastpage :
1885
Abstract :
The goal of this paper is to solve the following basic problem: Given discrete noisy samples from a continuous signal, compute the probability distribution of its distance from a fixed template. As opposed to the typical restoration problem, which considers a single optimal signal, the computation of the entire probability distribution necessitates integrating over the entire signal space. To achieve this, we apply path integration techniques. The problem is studied in one and two dimensions, and an accurate solution as well as an efficient approximation scheme are provided.
Keywords :
Noise measurement; Pattern matching; Physics; Probabilistic logic; Probability distribution; Uncertainty; Pattern matching; distance between signals; energy of a signal; path integrals.; probability; regularization; sampling;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2011.284
Filename :
6122033
Link To Document :
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