Joint Face Representation Adaptation and Clustering in Videos

2016 ◽  
pp. 236-251 ◽  
Author(s):  
Zhanpeng Zhang ◽  
Ping Luo ◽  
Chen Change Loy ◽  
Xiaoou Tang
Keyword(s):  
Face Representation

scholarly journals View-tuned and view-invariant face encoding in IT cortex is explained by selected natural image fragments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yunjun Nam ◽  
Takayuki Sato ◽  
Go Uchida ◽  
Ekaterina Malakhova ◽  
Shimon Ullman ◽  
...  
Keyword(s):  
Face Recognition ◽  
Visual Pathway ◽  
Visual Features ◽  
Natural Image ◽  
Face Representation ◽  
Low Level ◽  
Ventral Visual Pathway ◽  
Neural Substrate ◽  
The Face

AbstractHumans recognize individual faces regardless of variation in the facial view. The view-tuned face neurons in the inferior temporal (IT) cortex are regarded as the neural substrate for view-invariant face recognition. This study approximated visual features encoded by these neurons as combinations of local orientations and colors, originated from natural image fragments. The resultant features reproduced the preference of these neurons to particular facial views. We also found that faces of one identity were separable from the faces of other identities in a space where each axis represented one of these features. These results suggested that view-invariant face representation was established by combining view sensitive visual features. The face representation with these features suggested that, with respect to view-invariant face representation, the seemingly complex and deeply layered ventral visual pathway can be approximated via a shallow network, comprised of layers of low-level processing for local orientations and colors (V1/V2-level) and the layers which detect particular sets of low-level elements derived from natural image fragments (IT-level).

Spanning the Face Space

1998 ◽  
Vol 06 (03) ◽  
pp. 265-279 ◽  
Author(s):  
Shimon Edelman
Keyword(s):  
Computational Modeling ◽  
Object Representation ◽  
Receptive Fields ◽  
Computational Approach ◽  
Face Representation ◽  
Comprehensive Theory ◽  
Visual Areas ◽  
The Face ◽  
Higher Visual Areas ◽  
Perceptual Systems

The paper outlines a computational approach to face representation and recognition, inspired by two major features of biological perceptual systems: graded-profile overlapping receptive fields, and object-specific responses in the higher visual areas. This approach, according to which a face is ultimately represented by its similarities to a number of reference faces, led to the development of a comprehensive theory of object representation in biological vision, and to its subsequent psychophysical exploration and computational modeling.

Bimode model for face recognition and face representation

2011 ◽  
Vol 74 (5) ◽  
pp. 741-748 ◽  
Author(s):  
Hui Yan ◽  
Jian Yang ◽  
Jingyu Yang
Keyword(s):  
Face Recognition ◽  
Face Representation
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