title: Biologically inspired face recognition: toward pose-invariance.
abstract: A small change in image will cause a dramatic change in signals. Visual system is required to be able to ignore these changes, yet specific enough to perform recognition. This work intends to provide biological-backed insights into 2D translation and scaling invariance and 3D pose-invariance without imposing strain on memory and with biological justification. 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 is mainly based on current psychophysical evidences.
authors.affiliation: Centre of Diploma Programmes, Multimedia University, JalanAyerKeroh Lama, Melaka, Malaysia. nwtay@mmu.edu.my
authors.forename: Noel Tay Nuo
authors.initials: NT
authors.lastname: Wi
authors.forename: Chu Kiong
authors.initials: CK
authors.lastname: Loo
authors.forename: Letchumanan
authors.initials: L
authors.lastname: Chockalingam
mesh_terms: D003198:Computer Simulation / Q000706:statistics & numerical data*; D005145:Face; D006801:Humans; D008959:Models, Neurological; D010364:Pattern Recognition, Visual / Q000502:physiology*; D021641:Recognition, Psychology / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology