Face processing : human perception and principal components analysis
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TLDR
It is concluded that shape and “texture” (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system.Abstract:
Principal components analysis (PCA) of face images is here related to subjects’ performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those that had appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not correlate: Those faces easy to identify as being “seen” were unrelated to those faces easy to reject as being “unseen.” PCA was performed on three data sets: (1) face images with eye position standardized, (2) face images morphed to a standard template to remove shape information, and (3) the shape information from faces only. Analyses based on PCA of shape-free faces gave high predictions of FPs, whereas shape information itself contributed only to hits. Furthermore, whereas FPs were generally predictable from components early in the PCA, hits appeared to be accounted for by later components. We conclude that shape and “texture” (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system.read more
Citations
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Journal ArticleDOI
Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex
James V. Haxby,M. Ida Gobbini,Maura L. Furey,Alumit Ishai,Jennifer L. Schouten,Pietro Pietrini +5 more
TL;DR: The functional architecture of the object vision pathway in the human brain was investigated using functional magnetic resonance imaging to measure patterns of response in ventral temporal cortex while subjects viewed faces, cats, five categories of man-made objects, and nonsense pictures, and a distinct pattern of response was found for each stimulus category.
Journal ArticleDOI
Sparse Principal Component Analysis
TL;DR: This work introduces a new method called sparse principal component analysis (SPCA) using the lasso (elastic net) to produce modified principal components with sparse loadings and shows that PCA can be formulated as a regression-type optimization problem.
Journal ArticleDOI
Understanding the recognition of facial identity and facial expression
Andrew J. Calder,Andrew W. Young +1 more
TL;DR: A dominant view in face-perception research has been that the recognition of facial identity and facial expression involves separable visual pathways at the functional and neural levels, and data from experimental, neuropsychological, functional imaging and cell-recording studies are commonly interpreted within this framework.
Journal ArticleDOI
What is special about face recognition? nineteen experiments on a person with visual object agnosia and dyslexia but normal face recognition
TL;DR: It is concluded that face recognition normally depends on two systems: a holistic, face-specific system that is dependent on orientationspecific coding of second-order relational features (internal) and a part-based object-recognition system, which is damaged in CK and which contributes to face recognition when the face stimulus does not satisfy the domain-specific conditions needed to activate the face system.
Journal ArticleDOI
Recognition of unfamiliar faces
TL;DR: The relationships between different parts of the face (its 'configuration') are as important to the impression created of an upright face as the local features themselves, suggesting further constraints on the representations derived from faces.
References
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Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Journal ArticleDOI
Recognition-by-Components: A Theory of Human Image Understanding.
TL;DR: Recognition-by-components (RBC) provides a principled account of the heretofore undecided relation between the classic principles of perceptual organization and pattern recognition.
Journal ArticleDOI
Understanding face recognition
Vicki Bruce,Andrew W. Young +1 more
TL;DR: A functional model is proposed in which structural encoding processes provide descriptions suitable for the analysis of facial speech, for analysis of expression and for face recognition units, and it is proposed that the cognitive system plays an active role in deciding whether or not the initial match is sufficiently close to indicate true recognition.
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Application of the Karhunen-Loeve procedure for the characterization of human faces
Michael Kirby,Lawrence Sirovich +1 more
TL;DR: The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion, which results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix.
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Face recognition: features versus templates
Roberto Brunelli,Tomaso Poggio +1 more
TL;DR: Two new algorithms for computer recognition of human faces, one based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second based on almost-gray-level template matching are presented.