Face recognition impairments despite normal holistic processing and face space coding: Evidence from a case of developmental prosopagnosia

2010 ◽  
Vol 27 (8) ◽  
pp. 636-664 ◽  
Author(s):  
Tirta Susilo ◽  
Elinor McKone ◽  
Hugh Dennett ◽  
Hayley Darke ◽  
Romina Palermo ◽  
...  
Keyword(s):  
Face Recognition ◽  
Holistic Processing ◽  
Face Space ◽  
Space Coding

Holistic processing and unitization in face recognition memory.

2019 ◽  
Vol 148 (8) ◽  
pp. 1386-1406 ◽  
Author(s):  
Mitchell A. Meltzer ◽  
James C. Bartlett
Keyword(s):  
Face Recognition ◽  
Recognition Memory ◽  
Holistic Processing

Complement component face space for 3D face recognition from range images

2020 ◽  
Author(s):  
Koushik Dutta ◽  
Debotosh Bhattacharjee ◽  
Mita Nasipuri ◽  
Ondrej Krejcar
Keyword(s):  
Face Recognition ◽  
Complement Component ◽  
3D Face Recognition ◽  
Range Images ◽  
3D Face ◽  
Face Space

Adaptive face space coding in congenital prosopagnosia: Typical figural aftereffects but abnormal identity aftereffects

2011 ◽  
Vol 49 (14) ◽  
pp. 3801-3812 ◽  
Author(s):  
Romina Palermo ◽  
Davide Rivolta ◽  
C. Ellie Wilson ◽  
Linda Jeffery
Keyword(s):  
Face Space ◽  
Congenital Prosopagnosia ◽  
Space Coding

scholarly journals Face-Space: A Unifying Concept in Face Recognition Research

2016 ◽  
Vol 69 (10) ◽  
pp. 1996-2019 ◽  
Author(s):  
Tim Valentine ◽  
Michael B. Lewis ◽  
Peter J. Hills
Keyword(s):  
Face Recognition ◽  
Face Space

scholarly journals How Familiarity Warps Representation in Face Space

2018 ◽  
Author(s):  
Vassiki Chauhan ◽  
M. Ida Gobbini
Keyword(s):  
Face Recognition ◽  
Structural Features ◽  
Image Distortion ◽  
Face Space ◽  
Familiar Face ◽  
Unfamiliar Faces

AbstractRecognition of familiar as compared to unfamiliar faces is robust and resistant to marked image distortion or degradation. Here we tested the flexibility of familiar face recognition with a morphing paradigm where the appearance of a personally familiar face was mixed with the appearance of a stranger. The aim was to assess how categorical boundaries for recognition of identity are affected by familiarity. We found a narrower categorical boundary for the identity of personally familiar faces when they were mixed with unfamiliar identities as compared to the control condition, in which the appearance of two unfamiliar faces were mixed. Our results suggest that familiarity warps the representational geometry of face space, amplifying perceptual distances for small changes in the appearance of familiar faces that are inconsistent with the structural features that define their identities.

scholarly journals FACE RECOGNITION SYSTEM BY IMAGE PROCESSING

2020 ◽  
Author(s):  
Bilal Salih Abed Alhayani ◽  
Milind Rane
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Radon Transform ◽  
Wavelet Transforms ◽  
Low Frequency ◽  
Principal Component ◽  
Recognition System ◽  
Face Space ◽  
Legitimate User ◽  
Face Images

A wide variety of systems require reliable person recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that only a legitimate user and no one else access the rendered services. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. Face can be used as Biometrics for person verification. Face is a complex multidimensional structure and needs a good computing techniques for recognition. We treats face recognition as a two-dimensional recognition problem. A well-known technique of Principal Component Analysis (PCA) is used for face recognition. Face images are projected onto a face space that encodes best variation among known face images. The face space is defined by Eigen face which are eigenvectors of the set of faces, which may not correspond to general facial features such as eyes, nose, lips. The system performs by projecting pre extracted face image onto a set of face space that represent significant variations among known face images. The variable reducing theory of PCA accounts for the smaller face space than the training set of face. A Multire solution features based pattern recognition system used for face recognition based on the combination of Radon and wavelet transforms. As the Radon transform is in-variant to rotation and a Wavelet Transform provides the multiple resolution. This technique is robust for face recognition. The technique computes Radon projections in different orientations and captures the directional features of face images. Further, the wavelet transform applied on Radon space provides multire solution features of the facial images. Being the line integral, Radon transform improves the low-frequency components that are useful in face recognition

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