scholarly journals Comparing Face and Object Processing in Perception and Recognition

2021 ◽  
Author(s):  
Narjes Soltani Dehaghani ◽  
◽  
Burkhard Maess ◽  
Reza Khosrowabadi ◽  
Mojtaba Zarei ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Face Processing ◽  
Peak Time ◽  
Levels Of Processing ◽  
Object Processing ◽  
Amount Of Information ◽  
Facial Processing ◽  
The Face ◽  
Face Selectivity ◽  
Human Faces

Faces can be speedily processed, although they convey an immense amount of information. Hence, in psychophysiological experiments, human faces constitute very special stimuli! Numerous studies have investigated the electrophysiological correlates of face processing, showing the existence of multiple event-related components. Nevertheless, dissimilarities in various levels of processing are still controversial. In this present study, we used magnetoencephalography (MEG) to examine how facial processing is different in perception and recognition from object processing and also determined 95% confidence interval for the onset and peak time of the effects we found. Our results confirm the face-selectivity for the M170 component, but not always for the M100 component. Additionally, we observed a unique speed pattern for the M170 component in perception and recognition both at the onset and the peak time.

Biometrical Processing of Faces in Security and Forensics

2010 ◽  
pp. 79-103
Author(s):  
Pawel T. Puslecki
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Face Processing ◽  
Facial Features ◽  
Comprehensive Description ◽  
Facial Processing ◽  
Human Faces

The aim of this chapter is the overall and comprehensive description of the machine face processing issue and presentation of its usefulness in security and forensic applications. The chapter overviews the methods of face processing as the field deriving from various disciplines. After a brief introduction to the field, the conclusions concerning human processing of faces that have been drawn by the psychology researchers and neuroscientists are described. Then the most important tasks related to the computer facial processing are shown: face detection, face recognition and processing of facial features, and the main strategies as well as the methods applied in the related fields are presented. Finally, the applications of digital biometrical processing of human faces are presented.

Neural Responses to Facial Expression and Face Identity in the Monkey Amygdala

2007 ◽  
Vol 97 (2) ◽  
pp. 1671-1683 ◽  
Author(s):  
K. M. Gothard ◽  
F. P. Battaglia ◽  
C. A. Erickson ◽  
K. M. Spitler ◽  
D. G. Amaral
Keyword(s):  
Facial Expression ◽  
Firing Rate ◽  
Face Processing ◽  
Neural Responses ◽  
Firing Rates ◽  
Face Identity ◽  
Relative Contribution ◽  
The Face ◽  
Face Stimuli ◽  
Human Faces

The amygdala is purported to play an important role in face processing, yet the specificity of its activation to face stimuli and the relative contribution of identity and expression to its activation are unknown. In the current study, neural activity in the amygdala was recorded as monkeys passively viewed images of monkey faces, human faces, and objects on a computer monitor. Comparable proportions of neurons responded selectively to images from each category. Neural responses to monkey faces were further examined to determine whether face identity or facial expression drove the face-selective responses. The majority of these neurons (64%) responded both to identity and facial expression, suggesting that these parameters are processed jointly in the amygdala. Large fractions of neurons, however, showed pure identity-selective or expression-selective responses. Neurons were selective for a particular facial expression by either increasing or decreasing their firing rate compared with the firing rates elicited by the other expressions. Responses to appeasing faces were often marked by significant decreases of firing rates, whereas responses to threatening faces were strongly associated with increased firing rate. Thus global activation in the amygdala might be larger to threatening faces than to neutral or appeasing faces.

scholarly journals Awake fMRI reveals a specialized region in dog temporal cortex for face processing

2015 ◽  
Author(s):  
Daniel D Dilks ◽  
Peter Cook ◽  
Samuel K Weiller ◽  
Helen P Berns ◽  
Mark H Spivak ◽  
...  
Keyword(s):  
Face Processing ◽  
Temporal Cortex ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Everyday Objects ◽  
Face Area ◽  
Face Selectivity ◽  
Behavioral Evidence ◽  
Specialized Region ◽  
Human Faces

Recent behavioral evidence suggests that dogs, like humans and monkeys, are capable of visual face recognition. But do dogs also exhibit specialized cortical face regions similar to humans and monkeys? Using functional magnetic resonance imaging (fMRI) in six dogs trained to remain motionless during scanning without restraint or sedation, we found a region in the canine temporal lobe that responded significantly more to movies of human faces than to movies of everyday objects. Next, using a new stimulus set to investigate face selectivity in this predefined candidate dog face area, we found that this region responded similarly to images of human faces and dog faces, yet significantly more to both human and dog faces than to images of objects. Such face selectivity was not found in dog primary visual cortex. Taken together, these findings: 1) provide the first evidence for a face-selective region in the temporal cortex of dogs, which cannot be explained by simple low-level visual feature extraction; 2) reveal that neural machinery dedicated to face processing is not unique to primates; and 3) may help explain dogs’ exquisite sensitivity to human social cues.

scholarly journals Progress in perceptual research: the case of prosopagnosia

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 765 ◽  
Author(s):  
Andrea Albonico ◽  
Jason Barton
Keyword(s):  
Face Processing ◽  
Word Processing ◽  
Brain Lesion ◽  
Structural Basis ◽  
Object Processing ◽  
The Status ◽  
The Face ◽  
The Many ◽  
Developmental Variant ◽  
Neuroimaging Techniques

Prosopagnosia is an impairment in the ability to recognize faces and can be acquired after a brain lesion or occur as a developmental variant. Studies of prosopagnosia make important contributions to our understanding of face processing and object recognition in the human visual system. We review four areas of advances in the study of this condition in recent years. First are issues surrounding the diagnosis of prosopagnosia, including the development and evaluation of newer tests and proposals for diagnostic criteria, especially for the developmental variant. Second are studies of the structural basis of prosopagnosia, including the application of more advanced neuroimaging techniques in studies of the developmental variant. Third are issues concerning the face specificity of the defect in prosopagnosia, namely whether other object processing is affected to some degree and in particular the status of visual word processing in light of recent predictions from the “many-to-many hypothesis”. Finally, there have been recent rehabilitative trials of perceptual learning applied to larger groups of prosopagnosic subjects that show that face impairments are not immutable in this condition.

scholarly journals Specialization of Neural Mechanisms Underlying Face Recognition in Human Infants

2002 ◽  
Vol 14 (2) ◽  
pp. 199-209 ◽  
Author(s):  
Michelle de Haan ◽  
Olivier Pascalis ◽  
Mark H. Johnson
Keyword(s):  
Face Recognition ◽  
Postnatal Development ◽  
Face Processing ◽  
Nonhuman Primates ◽  
Newborn Infants ◽  
Event Related Potential ◽  
Neural Mechanisms ◽  
Human Infants ◽  
The Face ◽  
Human Faces

Newborn infants respond preferentially to simple face-like patterns, raising the possibility that the face-specific regions identified in the adult cortex are functioning from birth. We sought to evaluate this hypothesis by characterizing the specificity of infants' electrocortical responses to faces in two ways: (1) comparing responses to faces of humans with those to faces of nonhuman primates; and 2) comparing responses to upright and inverted faces. Adults' face-responsive N170 event-related potential (ERP) component showed specificity to upright human faces that was not observable at any point in the ERPs of infants. A putative “infant N170” did show sensitivity to the species of the face, but the orientation of the face did not influence processing until a later stage. These findings suggest a process of gradual specialization of cortical face processing systems during postnatal development.

scholarly journals Awake fMRI reveals a specialized region in dog temporal cortex for face processing

2015 ◽  
Author(s):  
Daniel D Dilks ◽  
Peter Cook ◽  
Samuel K Weiller ◽  
Helen P Berns ◽  
Mark H Spivak ◽  
...  
Keyword(s):  
Face Processing ◽  
Temporal Cortex ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Everyday Objects ◽  
Face Area ◽  
Face Selectivity ◽  
Behavioral Evidence ◽  
Specialized Region ◽  
Human Faces

Recent behavioral evidence suggests that dogs, like humans and monkeys, are capable of visual face recognition. But do dogs also exhibit specialized cortical face regions similar to humans and monkeys? Using functional magnetic resonance imaging (fMRI) in six dogs trained to remain motionless during scanning without restraint or sedation, we found a region in the canine temporal lobe that responded significantly more to movies of human faces than to movies of everyday objects. Next, using a new stimulus set to investigate face selectivity in this predefined candidate dog face area, we found that this region responded similarly to images of human faces and dog faces, yet significantly more to both human and dog faces than to images of objects. Such face selectivity was not found in dog primary visual cortex. Taken together, these findings: 1) provide the first evidence for a face-selective region in the temporal cortex of dogs, which cannot be explained by simple low-level visual feature extraction; 2) reveal that neural machinery dedicated to face processing is not unique to primates; and 3) may help explain dogs’ exquisite sensitivity to human social cues.

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.

scholarly journals Charged With a Crime: The Neuronal Signature of Processing Negatively Evaluated Faces Under Different Attentional Conditions

2021 ◽  
pp. 095679762199666
Author(s):  
Sebastian Schindler ◽  
Maximilian Bruchmann ◽  
Claudia Krasowski ◽  
Robert Moeck ◽  
Thomas Straube
Keyword(s):  
Event Related Potentials ◽  
Emotional Information ◽  
Early Posterior Negativity ◽  
Information Studies ◽  
The Face ◽  
Related Potentials ◽  
Feature Based ◽  
Human Faces ◽  
Emotional Knowledge ◽  
Late Stages

Our brains rapidly respond to human faces and can differentiate between many identities, retrieving rich semantic emotional-knowledge information. Studies provide a mixed picture of how such information affects event-related potentials (ERPs). We systematically examined the effect of feature-based attention on ERP modulations to briefly presented faces of individuals associated with a crime. The tasks required participants ( N = 40 adults) to discriminate the orientation of lines overlaid onto the face, the age of the face, or emotional information associated with the face. Negative faces amplified the N170 ERP component during all tasks, whereas the early posterior negativity (EPN) and late positive potential (LPP) components were increased only when the emotional information was attended to. These findings suggest that during early configural analyses (N170), evaluative information potentiates face processing regardless of feature-based attention. During intermediate, only partially resource-dependent, processing stages (EPN) and late stages of elaborate stimulus processing (LPP), attention to the acquired emotional information is necessary for amplified processing of negatively evaluated faces.

scholarly journals Facial Feature Model for a Portrait Video Stylization

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 442 ◽  
Author(s):  
Dongxue Liang ◽  
Kyoungju Park ◽  
Przemyslaw Krompiec
Keyword(s):  
Facial Feature ◽  
Feature Model ◽  
Facial Features ◽  
Outer Face ◽  
Flow Estimation ◽  
Photorealistic Rendering ◽  
Stroke Models ◽  
The Face ◽  
Face Contour ◽  
Human Faces

With the advent of the deep learning method, portrait video stylization has become more popular. In this paper, we present a robust method for automatically stylizing portrait videos that contain small human faces. By extending the Mask Regions with Convolutional Neural Network features (R-CNN) with a CNN branch which detects the contour landmarks of the face, we divided the input frame into three regions: the region of facial features, the region of the inner face surrounded by 36 face contour landmarks, and the region of the outer face. Besides keeping the facial features region as it is, we used two different stroke models to render the other two regions. During the non-photorealistic rendering (NPR) of the animation video, we combined the deformable strokes and optical flow estimation between adjacent frames to follow the underlying motion coherently. The experimental results demonstrated that our method could not only effectively reserve the small and distinct facial features, but also follow the underlying motion coherently.

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