de.mpg.escidoc.pubman.appbase.FacesBean
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Vortrag

Pixel-based versus correspondence-based representations of human faces: Implications for sex discrimination

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84263

Troje,  NF
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84280

Vetter,  T
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Troje, N., & Vetter, T. (1996). Pixel-based versus correspondence-based representations of human faces: Implications for sex discrimination. Talk presented at 19th European Conference on Visual Perception. Strasbourg, France.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-EB3E-5
Zusammenfassung
In human perception, as well as in machine vision, a crucial step in solving any object recognition task is an appropriate description of the object class under consideration. We emphasise this issue when considering the object class `human faces'. We discuss different representations that can be characterised by the degree of alignment between the images they provide for. The representations used span the whole range between a purely pixel-based image representation and a sophisticated model-based representation derived from the pixel-to-pixel correspondence between the faces [Vetter and Troje, 1995, in Mustererkennung Eds G Sagerer, S Posch, F Kummert (Berlin: Springer)]. The usefulness of these representations for sex classification was compared. This was done by first applying a Karhunen -- Loewe transformation on the representation to orthogonalise the data. A linear classifier was trained by means of a gradient-descent procedure. The classification error in a completely cross-validated simulation ranged from 15 in the simplest version of the pixel-based representation to 2.5 for the correspondence-based representation. However, even with intermediate representations very good performance was achieved.