HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
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.
Document type :
Conference papers
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download

Contributor : Ioan Marius Bilasco Connect in order to contact the contributor
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


Automatic Facial Feature Detec...
Files produced by the author(s)


  • HAL Id : hal-00812308, version 1


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⟩



Record views


Files downloads