NDLI: Biological inspired pose-invariant face recognition

Content Provider	IEEE Xplore Digital Library
Author	Noel Tay Nuo Wi Loo Chu Kiong
Copyright Year	2012
Description	Author affiliation: Multi-Media University, Ayer Keroh, 75450, Melaka, Malaysia (Noel Tay Nuo Wi) \|\| Department of Artificial Intelligence, Faculty of Computer Science & Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia (Loo Chu Kiong)
Abstract	A small change in image will cause a dramatic change in signals. Visual system needs to ignore these changes, yet specific enough to perform recognition. Problem intended to be solved is on 2D translation and scaling invariances and 3D pose invariance without imposing strain on memory and with biological justification. In this paper, we propose a novel biologically inspired vision model for pose-invariant face recognition. The model can be divided into lower and higher visual stages. Lower visual stage models the visual pathway from retina to the striate cortex (V1), whereas the modeling of higher visual stage mainly based on current psychophysical. The feasibility of the proposed model is evidenced by the evaluation study using FERRET face database.
Starting Page	1
Ending Page	6
File Size	325157
Page Count	6
File Format	PDF
ISBN	9781467344975
ISSN	21544824
e-ISBN	9781889334479
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-24
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	TSI Press
Subject Keyword	Visualization Brain modeling Face recognition Biological system modeling Manifolds Visual systems Biologically-inspired vision hierarchy invariance Invariant face recognition
Content Type	Text
Resource Type	Article

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