Sensors 2013, 13(12), 16682-16713; doi:10.3390/s131216682

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

1 UC Lab, Department of Computer Engineering, Kyung Hee University, Yongin-Si 446-701, Korea 2 Division of Information and Computer Engineering, Ajou University, Suwon 443-749, Korea
* Author to whom correspondence should be addressed.
Received: 28 October 2013; in revised form: 30 November 2013 / Accepted: 2 December 2013 / Published: 5 December 2013
(This article belongs to the Section Physical Sensors)
PDF Full-text Download PDF Full-Text [1156 KB, uploaded 5 December 2013 11:30 CET]
Abstract: Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.
Keywords: face detection; GHE; facial expressions; PCA; ICA; LDA; HMMs

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

MDPI and ACS Style

Siddiqi, M.H.; Lee, S.; Lee, Y.-K.; Khan, A.M.; Truc, P.T.H. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems. Sensors 2013, 13, 16682-16713.

AMA Style

Siddiqi MH, Lee S, Lee Y-K, Khan AM, Truc PTH. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems. Sensors. 2013; 13(12):16682-16713.

Chicago/Turabian Style

Siddiqi, Muhammad H.; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil M.; Truc, Phan T.H. 2013. "Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems." Sensors 13, no. 12: 16682-16713.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert