scholarly journals Optimal matching problem in detection and recognition performance evaluation

2002 ◽  
Vol 35 (10) ◽  
pp. 2125-2139 ◽  
Author(s):  
Gang Liu ◽  
Robert M. Haralick
1992 ◽  
Vol 35 (4) ◽  
pp. 942-949 ◽  
Author(s):  
Christopher W. Turner ◽  
David A. Fabry ◽  
Stephanie Barrett ◽  
Amy R. Horwitz

This study examined the possibility that hearing-impaired listeners, in addition to displaying poorer-than-normal recognition of speech presented in background noise, require a larger signal-to-noise ratio for the detection of the speech sounds. Psychometric functions for the detection and recognition of stop consonants were obtained from both normal-hearing and hearing-impaired listeners. Expressing the speech levels in terms of their short-term spectra, the detection of consonants for both subject groups occurred at the same signal-to-noise ratio. In contrast, the hearing-impaired listeners displayed poorer recognition performance than the normal-hearing listeners. These results imply that the higher signal-to-noise ratios required for a given level of recognition by some subjects with hearing loss are not due in part to a deficit in detection of the signals in the masking noise, but rather are due exclusively to a deficit in recognition.


2000 ◽  
Vol 37 (02) ◽  
pp. 494-503
Author(s):  
Ludger Rüschendorf ◽  
Gernot Sachs

Partitioning algorithms for the Euclidean matching and for the semi-matching problem in the plane are introduced and analysed. The algorithms are analogues of Karp's well-known dissection algorithm for the travelling salesman problem. The algorithms are proved to run in time nlogn and to approximate the optimal matching in the probabilistic sense. The analysis is based on the techniques developed in Karp (1977) and on the limit theorem of Redmond and Yukich (1993) for quasiadditive functionals.


2014 ◽  
Vol 548-549 ◽  
pp. 939-942 ◽  
Author(s):  
Mi Young Cho ◽  
Young Sook Jeong ◽  
Byung Tae Chun

With the increasing of service robots, human-robot interaction for natural communication between user and robot is becoming more and more important. Especially, face recognition is a key issue of HRI. Even though robots mainly use face detection and recognition to provide various services, it is still difficult to guarantee of performance due to insufficient test methods in point of view robot. So, we propose a new performance evaluation method for robot using LED monitor.


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