A Study of Local Binary Pattern Method for Facial Expression Detection

International Journal of Computer Trends and Technology (IJCTT)          
© 2014 by IJCTT Journal
Volume-7 Number-3                          
Year of Publication : 2014
Authors : Ms.Drashti H. Bhatt , Mr.Kirit R. Rathod , Mr.Shardul J. Agravat
DOI :  10.14445/22312803/IJCTT-V7P143


      Ms.Drashti H. Bhatt , Mr.Kirit R. Rathod , Mr.Shardul J. Agravat. Article: A Study of Local Binary Pattern Method for Facial Expression Detection. International Journal of Computer Trends and Technology (IJCTT) 7(3):151-153, January 2014. Published by Seventh Sense Research Group.

      Face detection is a basic task for expression recognition. The reliability of face detection & face recognition approach has a major role on the performance and usability of the entire system. There are several ways to undergo face detection & recognition. We can use Image Processing Operations, various classifiers, filters or virtual machines for the former. Various strategies are being available for Facial Expression Detection. The field of facial expression detection can have various applications along with its importance & can be interacted between human being & computer. Many few options are available to identify a face in an image in accurate & efficient manner. Local Binary Pattern (LBP) based texture algorithms have gained popularity in these years. LBP is an effective approach to have facial expression recognition & is a feature-based approach.

[1] Mikael Nilsson, “Face Detection”, Presentation.
[2] Caifeng Shan, Shaogang Gong, Peter W. McOwan, “Facial expression recognition based on Local Binary Patterns: A comprehensive study”, published in ELAEVIER Journal.
[3] Yao-Jiunn Chen, Yen-Chun Lin, “Simple Face-detection Algorithm Based on Minimum Facial Features”, in The 33rd Annual Conference of the IEEE Industrial Electronics Society.
[4] Yu-Ting Pai, Shanq-Jang Ruan, Mon-ChauShie, Yi-Chi Liu, “A Simple and Accurate Color Face Detection Algorithm in Complex Background”, in 2006 IEEE.
[5] Di Huang, Student Member, IEEE, Caifeng Shan, Member, IEEE, Mohsen Ardabilian, “Local Binary Patterns and Its Application to Facial Image Analysis: A Survey”, published in IEEE 2011 November.
[6] Yuichiro Tajima, Koichi Ito, Takafumi Aoki, “Performance Improvement of Face Recognition Algorithms Using Occluded-Region Detection”, published in 2013 IEEE.
[7] PENG Zhao-yi, WEN Zhi-qiang, ZHOU Yu , “Application of Mean Shift Algorithm in Real-time Facial Expression Recognition”, in Education Department Foundation of Hunan Province (No. 09C324,“Research on multi-pose real-time facial expression recognition”)
[8] Vinay Kumar B, A Project on “Face Recognition Using Gabor Wavelets” in Visvesvaraya Technological University, Belgaum project
[9] http://en.wikipedia.org/wiki/Face_detection
[10] http://www.slideshare.net/sadique_ghitm/face-recognition-a-comparison-of-appearance-based-approaches.

Keywords-Local Binary Patterns (LBP), Face Recognition, Expression Detection.