Audiovisual Emotion Recognition Using Semi-Coupled Hidden Markov Model with State-Based Alignment Strategy

Chung Hsien Wu, Jen Chun Lin, Wen Li Wei

研究成果: Chapter

摘要

This chapter introduces the current data fusion strategies among audiovisual signals for bimodal emotion recognition. Face detection, in the chapter, is performed based on the adaboost cascade face detector and can be used to provide initial facial position and reduce the time for error convergence in feature extraction. In the chapter, active appearance model (AAM) is employed to extract the 68 labeled facial feature points (FPs) from 5 facial regions including eyebrow, eye, nose, mouth, and facial contours for later facial animation parameters (FAPs) calculation. Three kinds of primary prosodic features are adopted, including pitch, energy, and formants F1-F5 in each speech frame for emotion recognition. Finally, a semi-coupled hidden Markov model (SC-HMM) is proposed for emotion recognition based on state-based alignment strategy for audiovisual bimodal features.

原文English
主出版物標題Emotion Recognition
主出版物子標題A Pattern Analysis Approach
發行者wiley
頁面493-513
頁數21
ISBN(電子)9781118910566
ISBN(列印)9781118130667
DOIs
出版狀態Published - 2015 一月 2

All Science Journal Classification (ASJC) codes

  • 工程 (全部)
  • 電腦科學(全部)

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