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Facial expression recognition with support vector machines

  • This thesis investigates methods for the recognition of facial expressions using support vector machines. Rather than trying to recognize facial actions in the face such as raised eyebrow, mouth open and frowns. These facial actions are described in the Facial Action Coding System (FACS) and are essential facial components, which can be combined to form facial expressions. We perform independent recognition of 6 upper and 10 lower action units in the face, which may occur either individually or in combination. Based on a feature extraction from grey-level values, the system is expected to recognize under real-time conditions. Results are presented with different image resolutions, SVM kernels and variations of low-level features.

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Metadaten
Author:Martin Michael Schulze
Document Type:Master's Thesis
Language:English
Year of Publication:2002
Publishing Institution:HTWG Konstanz
Release Date:2003/08/15
Tag:facial expression recognition ; action unit recognition; Facial Action Coding System; support vector machines; low-level feature extraction
GND Keyword:Erkennung; Mund-Kiefer-Gesichtsbereich; Mimik; FACS; Codierung; Physiognomik
Institutes:Fakult├Ąt Informatik
DDC functional group:004 Informatik
Open Access?:Ja