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Abstract Automatic Facial Expression Recognition using Facial Animation Parameters and Mult.pdf

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Abstract Automatic Facial Expression Recognition using Facial Animation Parameters and Mult

Automatic Facial Expression Recognition using Facial Animation Parameters and Multi-Stream HMMs Petar S. Aleksic*, Member, IEEE, and Aggelos K. Katsaggelos, Fellow, IEEE Abstract The performance of an automatic facial expression recognition system can be significantly improved by modeling the reliability of different streams of facial expression information utilizing multi-stream hidden Markov models (HMMs). In this paper, we present an automatic multi-stream HMM facial expression recognition system and analyze its performance. The proposed system utilizes facial animation parameters (FAPs), supported by the MPEG-4 standard, as features for facial expression classification. Specifically, the FAPs describing the movement of the outer-lips and eyebrows are used as observations. Experiments are first performed employing single-stream HMMs under several different scenarios, utilizing outer-lip and eyebrow FAPs individually and jointly. A multi-stream HMM approach is proposed for introducing facial expression and FAP group dependent stream reliability weights. The stream weights are determined based on the facial expression recognition results obtained when FAP streams are utilized individually. The proposed multi-stream HMM facial expression system, which utilizes stream reliability weights, achieves relative reduction of the facial expression recognition error of 44% compared to the single-stream HMM system. Index Terms- facial expression recognition, multi-stream HMMs, facial animation parameters Manuscript received July 1, 2004; revised February 6, 2005. An earlier version of this work appeared in [40]. P. S. Aleksic and A. K. Katsaggelos are with Electrical and Computer Engineering Department at Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA; phone: 847-491-3039; fax 847-491- 4455; emails: {apetar, aggk}@ece.northwestern.edu EDICS: 6-PATT (Pattern Recognition and Applications), 7-MMOD (Multimodal Human-Machine Inter