DocumentCode :
2173502
Title :
On comparing hard and soft fusion of dependent detectors
Author :
Soriano, Antonio ; Vergara, Luis ; Safont, Gonzalo ; Salazar, Adisson
Author_Institution :
Inst. de Telecomun. y Aplic. Multimedia (iTEAM), Univ. Politec. de Valencia (UPV), Valencia, Spain
fYear :
2012
fDate :
23-26 Sept. 2012
Firstpage :
1
Lastpage :
6
Abstract :
A detection problem, where we have a set of two types of different measurements or modalities of one event, is considered. The optimal fusion rule to combine both modalities in one detector needs the knowledge of the joint statistics of modalities. In many cases we do not know these joint statistics and it is usual to consider independence between modalities for implementing a suboptimal fusion rule. Another suboptimum alternative not much used is to make hard fusion, that is, to thresholding every modality to obtain a set of binary decisions to be fused in only on final decision. In some situations, we can obtain better results using hard fusion instead of soft fusion under the independence assumption. The goal of this paper is to show that the later sentence is generally true.
Keywords :
binary decision diagrams; sensor fusion; signal detection; statistical analysis; binary decisions; dependent detectors; different measurements; different modalities; hard fusion; independence assumption; joint statistics; soft fusion; suboptimal fusion rule; Abstracts; Detectors; Indexes; Decisions fusion; Detection problem; Hard fusion; Multimodal integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2012 IEEE International Workshop on
Conference_Location :
Santander
ISSN :
1551-2541
Print_ISBN :
978-1-4673-1024-6
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2012.6349792
Filename :
6349792
Link To Document :
بازگشت