Facial Expression Recognition using Entropy and Brightness Features - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

Facial Expression Recognition using Entropy and Brightness Features

(1) , (1) , (2) , (1)
1
2

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.
Fichier principal
Vignette du fichier
ISDA_FER_Final_manuscript.pdf (516.86 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

ujm-00632860 , version 1 (16-10-2011)

Identifiers

  • HAL Id : ujm-00632860 , version 1

Cite

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⟩
226 View
371 Download

Share

Gmail Facebook Twitter LinkedIn More