Facial expression recognition based on a weighted Local Binary Pattern

Author

Shoyaib, Mohammad ; Abdullah-Al-Wadud, M. ; Youl, Jo Moo ; Alam, Muhammad Mahbub ; Chae, Oksam

Author_Institution

Dept. of Comput. Eng., Kyung Hee Univ., Yongin, South Korea

fYear

2010

fDate

23-25 Dec. 2010

Firstpage

321

Lastpage

324

Abstract

We introduce a facial expression recognition method, which incorporates a weight to the Local Binary Pattern (LBP), and generates solid expression features. Furthermore, we use Adaboost to select a small set of prominent features, which is used by the Support Vector Machine (SVM) to classify facial expressions efficiently. Experimental results demonstrate that our method outperforms the state-of-the-art methods in terms of both accuracy and complexities.

Keywords

emotion recognition; face recognition; learning (artificial intelligence); support vector machines; Adaboost; SVM; facial expression recognition; support vector machine; weighted local binary pattern; Accuracy; Databases; Face recognition; Histograms; Kernel; Pixel; Support vector machine classification; Adaboost; Expression recognition; Local Binary Pattern; Prominent features; Support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology (ICCIT), 2010 13th International Conference on

Conference_Location

Dhaka

Print_ISBN

978-1-4244-8496-6

Type

conf

DOI

10.1109/ICCITECHN.2010.5723877

Filename

5723877

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2656870