TY - THES U1 - Master Thesis A1 - Schulze, Martin Michael T1 - Facial expression recognition with support vector machines N2 - 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. KW - Erkennung KW - Mund-Kiefer-Gesichtsbereich KW - Mimik KW - FACS KW - Codierung KW - Physiognomik KW - facial expression recognition ; action unit recognition KW - Facial Action Coding System KW - support vector machines KW - low-level feature extraction Y2 - 2002 ER -