Facial Expression Recognition using Entropy and Brightness Features

Abstract : This paper proposes a novel framework for universal facial expression recognition. The framework is based on two sets of features extracted from the face image: entropy and brightness. First, saliency maps are obtained by state-of-the-art saliency detection algorithm i.e. "frequencytuned salient region detection". Then only localized salient facial regions from saliency maps are processed to extract entropy and brightness features. To validate the performance of saliency detection algorithm against human visual system, we have performed a visual experiment. Eye movements of 15 subjects were recorded with an eye-tracker in free viewing conditions as they watch a collection of 54 videos selected from Cohn-Kanade facial expression database. Results of the visual experiment provided the evidence that obtained saliency maps conforms well with human fixations data. Finally, evidence of the proposed framework's performance is exhibited through satisfactory classification results on Cohn-Kanade database.
Complete list of metadatas

Cited literature [17 references]  Display  Hide  Download

https://hal-ujm.archives-ouvertes.fr/ujm-00632860
Contributor : Hubert Konik <>
Submitted on : Sunday, October 16, 2011 - 6:53:26 PM
Last modification on : Tuesday, February 26, 2019 - 3:37:58 PM
Long-term archiving on : Tuesday, January 17, 2012 - 2:21:18 AM

File

ISDA_FER_Final_manuscript.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : ujm-00632860, version 1

Citation

Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz. Facial Expression Recognition using Entropy and Brightness Features. 11th International Conference on Intelligent Systems Design and Applications (ISDA), Nov 2011, Cordoba, Spain. pp.1-6. ⟨ujm-00632860⟩

Share

Metrics

Record views

440

Files downloads

437