Obtaining reliable and complete systems able to extract human emotional status from streaming videos is of paramount importance to Human Machine Interaction (HMI) applications. Side views, unnatural postures and context are challenges. This paper presents a semi-supervised fuzzy emotional classification system based on Russell’s circumplex model. This emotional inference system relies only on face related features codified with the Facial Action Coding System (FACS). These features are provided by a morphable 3D tracking system robust to posture, occlusion and illumination changes.
Emotional state inference using face related features / M. Anisetti, V. Bellandi - In: New directions in intelligent interactive multimedia systems and services. 2. / [a cura di] E. Damiani ... [et al.].. - Berlin : Springer, 2009. - ISBN 9783642029363. - pp. 401-411
Emotional state inference using face related features
M. AnisettiPrimo
;V. BellandiUltimo
2009
Abstract
Obtaining reliable and complete systems able to extract human emotional status from streaming videos is of paramount importance to Human Machine Interaction (HMI) applications. Side views, unnatural postures and context are challenges. This paper presents a semi-supervised fuzzy emotional classification system based on Russell’s circumplex model. This emotional inference system relies only on face related features codified with the Facial Action Coding System (FACS). These features are provided by a morphable 3D tracking system robust to posture, occlusion and illumination changes.
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