Adaptively Nearest Feature Point Classifier for Face Recognition

2014 ◽  
pp. 115-122
Author(s):  
Qingxiang Feng ◽  
Jeng-Shyang Pan ◽  
Lijun Yan ◽  
Tien-Szu Pan
Keyword(s):  
Face Recognition ◽  
Feature Point

Enhanced retinal modeling for face recognition and facial feature point detection under complex illumination conditions

2016 ◽  
Vol 25 (4) ◽  
pp. 043028 ◽  
Author(s):  
Yong Cheng ◽  
Zuoyong Li ◽  
Liangbao Jiao ◽  
Hong Lu ◽  
Xuehong Cao
Keyword(s):  
Face Recognition ◽  
Facial Feature ◽  
Feature Point ◽  
Point Detection

Face Recognition by Geometrical Feature-Point Bilateral Matching

2013 ◽  
Vol 479-480 ◽  
pp. 883-888
Author(s):  
Yea Shuan Huang ◽  
Guo Da Peng
Keyword(s):  
Face Recognition ◽  
Detection Algorithm ◽  
Face Image ◽  
Feature Point ◽  
Feature Points ◽  
Salient Point ◽  
Recognition Result ◽  
Feature Based ◽  
Point Detection ◽  
Human Faces

This paper presents a novel feature-point bilateral recognition method for recognizing human faces. At first, from either an input face image or a reference face image, a set of distinct feature points is extracted by using a general salient point detection algorithm. Then, based on the detected feature points, a bilateral recognition is performed. Bilateral recognition means there are two ways of recognition, forward recognition and backward recognition. Finally, the forward score and the backward score are summed up into a bilateral score which is used to obtain recognition result. In order to perform recognition in real-time, we also use a GDA algorithm to select the possible candidates, and then use the proposed bilateral recognition operation to make the final recognition decision. Experiments on two famous face databases show that the proposed algorithm get excellence recognition result and is complementary to traditional global-feature-based face recognition methods.

scholarly journals Gabor Descriptors Extraction in the SURF Feature Point for Improvement Accuracy in Face Recognition

2012 ◽  
Vol 17 (5) ◽  
pp. 808-816
Author(s):  
Jae-Yong Lee ◽  
Ji-Eun Kim ◽  
Seoung-Jun Oh
Keyword(s):  
Face Recognition ◽  
Feature Point

Face Inversion Effect Emerges Under Critical Configural Discrepancy

2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger
Keyword(s):  
Face Recognition ◽  
Face Processing ◽  
Underlying Mechanism ◽  
Inversion Effect ◽  
Configural Processing ◽  
Major Contributor ◽  
Face Inversion Effect ◽  
Configural Information ◽  
Face Inversion ◽  
The Face

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.

Perceptual Effects and Recollective Experience in Face Recognition

2005 ◽  
Vol 52 (3) ◽  
pp. 224-231 ◽  
Author(s):  
Chrisanthi Nega
Keyword(s):  
Face Recognition ◽  
Recognition Memory ◽  
Congruency Effect ◽  
Facial Recognition ◽  
Memory Systems ◽  
Study Time ◽  
Perceptual Fluency ◽  
Recollective Experience ◽  
Trace Strength ◽  
Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

Proclivity to Choose on Face Recognition Predicts PTC on Lineups

2014 ◽  
Author(s):  
Mario Baldassari ◽  
Justin Kantner ◽  
D. Stephen Lindsay
Keyword(s):  
Face Recognition
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