Kalman Filter-Based Facial Emotional Expression Recognition

Autor:	Valentin Enescu, Isabel Gonzalez, Ping Fan, Hichem Sahli, Dongmei Jiang
Přispěvatelé:	D?mello, Sidney, Graesser, Arthur, Schuller, Björn, Martin, Jean-claud, Audio Visual Signal Processing, Electronics and Informatics
Rok vydání:	2011
Předmět:	State-transition matrix Extended Kalman filter Facial expression State-space representation Speech recognition computer science Emotional expression Kalman filter Psychology Computer animation Invariant extended Kalman filter
Zdroj:	Affective Computing and Intelligent Interaction ISBN: 9783642245992 ACII (1) Vrije Universiteit Brussel
DOI:	10.1007/978-3-642-24600-5_53
Popis:	In this work we examine the use of State-Space Models to model the temporal information of dynamic facial expressions. The later being represented by the 3D animation parameters which are recovered using 3D Candide model. The 3D animation parameters of an image sequence can be seen as the observation of a stochastic process which can be modeled by a linear State-Space Model, the Kalman Filter. In the proposed approach each emotion is represented by a Kalman Filter, with parameters being State Transition matrix, Observation matrix, State and Observation noise covariance matrices. Person-independent experimental results have proved the validity and the good generalization ability of the proposed approach for emotional facial expression recognition. Moreover, compared to the state-of-the-art techniques, the proposed system yields significant improvements in recognizing facial expressions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b473e38142b75496df011c19825aa74 https://doi.org/10.1007/978-3-642-24600-5_53 Zobrazit plný text záznamu