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Conference papers

Automatic Facial Feature Detection for Facial Expression Recognition

Abstract : This paper presents a real-time automatic facial feature point detection method for facial expression recognition. The system is capable of detecting seven facial feature points (eyebrows, pupils, nose, and corners of mouth) in grayscale images extracted from a given video. Extracted feature points then used for facial expression recognition. Neutral, happiness and surprise emotions have been studied on the Bosphorus dataset and tested on FG-NET video dataset using OpenCV. We compared our results with previous studies on this dataset. Our experiments showed that proposed method has the advantage of locating facial feature points automatically and accurately in real-time.
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Submitted on : Saturday, September 29, 2018 - 3:57:13 PM
Last modification on : Wednesday, May 11, 2022 - 12:34:02 PM
Long-term archiving on: : Monday, December 31, 2018 - 10:24:57 AM

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  • HAL Id : hal-00812308, version 1

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Taner Danisman, Ioan Marius Bilasco, Nacim Ihaddadene, Chaabane Djeraba. Automatic Facial Feature Detection for Facial Expression Recognition. Fifth International Conference on Computer Vision Theory and Applications (VISAPP) 2010, May 2010, Angers, France. pp.407-412. ⟨hal-00812308⟩

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