Efficient Recognition of Authentic Dynamic Facial Expressions on the Feedtum Database

In order to allow for fast recognition of a user’s affective state we discuss innovative holistic and self organizing approaches for efficient facial expression analysis. The feature set is thereby formed by global descriptors and MPEG based DCT coefficients. In view of subsequent classification we compare modelling by pseudo multidimensional Hidden Markov Models and Support Vector Machines. Within the latter case super-vectors are constructed based on Sequential Floating Search Methods. Extensive test-runs as a proof of concept are carried out on our publicly available FEEDTUM database consisting of elicited spontaneous emotions of 18 subjects within the MPEG-4 emotion-set plus added neutrality. Maximum recognition performance reaches the benchmark-rate gained by a human perception test with 20 test-persons and manifest the effectiveness of the introduced novel concepts.

• Type: Conference
• Year: 2006
• Where: ICMCS
• Authors: Frank Wallhoff, Björn Schuller, Michael Hawellek, Gerhard Rigoll
• Keywords: Efficient Facial Expression, ICMCS 2006, Mpeg Based Dct, Multidimensional Hidden Markov