Person recognition across multi-session and multi-exemplar images using ensemble of classifiers

Author(s):  
BILAL HASSAN ◽  
EBROUL IZQUIERDO
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.


Perception ◽  
10.1068/p5503 ◽  
2006 ◽  
Vol 35 (6) ◽  
pp. 761-773 ◽  
Author(s):  
Dana A Roark ◽  
Alice J O'Toole ◽  
Hervé Abdi ◽  
Susan E Barrett

1997 ◽  
Vol 50 (3) ◽  
pp. 498-517 ◽  
Author(s):  
Stefan R. Schweinberger ◽  
Anja Herholz ◽  
Volker Stief

Two experiments examined repetition priming in the recognition of famous voices. In Experiment 1, reaction times for fame decisions to famous voice samples were shorter than in an unprimed condition, when voices were primed by a different voice sample of the same person having been presented in an earlier phase of the experiment. No effect of voice repetition was observed for non-famous voices. In Experiment 2, it was investigated whether this priming effect is voice-specific or whether it is related to post-perceptual processes in person recognition. Recognizing a famous voice was again primed by having earlier heard a different voice sample of that person. Although an earlier exposure to that person's name did not cause any priming, there was some indication of priming following an earlier exposure to that person's face. Finally, earlier exposure to the identical voice sample (as compared to a different voice sample from the same person) caused a considerable bias towards responding “famous”—i.e. performance benefits for famous but costs for nonfamous voices. The findings suggest that (1) repetition priming invoice recognition primarily involves the activation of perceptual representations of voices, and (2) it is important to determine the conditions in which priming causes bias effects that need to be disentangled from performance benefits.


ETRI Journal ◽  
2015 ◽  
Author(s):  
Hye Jin Kim ◽  
Jaeyeon Lee ◽  
Do-Hyung Kim ◽  
Kee Young Kim
Keyword(s):  

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