Facial Expresiones Recognition

System: survey

Master's student Mohammed Abdul Rahman 

Basra UniversityCollege of Science

Department of Computer Science Under the supervision

d. Zainab Ibrahim

2015-2016

Out Line• The aim of research• Introduction• History (Introduction & Previous Works)• Importance of research and its Applications• Physically analysis• Challenges• Related works• Basic Structure of Facial Expression analysis• The proposed system• Conclusion• References

The aim of research• The research aims to design automatic system

to distinguish and read facial expressions ( i.e., happy, surprise, anger, sadness, fear, and disgust ).

• By use of smart computer programming for design and implementation of the proposed system.

The goal of the system design

Introduction• To make Human Computer Interaction (HCI)

more natural and friendly, it would be beneficial to give computers the ability to recognize situations the same way a human does.

• Over the last years, face recognition and automatic analysis of facial expressions has one of the most challenging research areas in the field of Computer vision and has received a special importance.

Introduction& Previous Works

• In recent years, a lot of work has been done on the affective recognition of expressions which holds the major key in the human-machine interaction.

• In 1872. The first suggestion of expression of emotions as universal was given by Charles Darwin in his contriving work build from his theory of evolution.

Introduction& Previous Works

• In 1971. The psychologist Ekman and Friesen showed in their cross culture studies that the six emotions .

• Several techniques have emerged in order to improve the efficiency of the recognition by addressing problems in face detection and extraction features in recognizing expressions.

Importance of research and its Applications

• Facial Expression recognition is an important technique and has drawn the attention of many researchers due to its varying applications such as security systems, medical systems, entertainment.

Importance of research and its Applications

• Such as Human Computer Interaction (HCI), Emotion analysis, Psychological area, virtual reality , video-conferencing, indexing and retrieval of image and video database, image understanding and synthetic face animation.

Physically analysis

• The movement of facial muscles areas

Challenges

• A human can detect face and recognition on facial expressions without effort , but for a machine and in Computer Vision it is very difficult . Why… ?

Challenges

• The main challenges in automatic affect recognition :

• Head-pose variations.• illumination variations.• Registration errors. • Occlusions.

Related works

• 2011 , P.D.Khandait , Dr. R.C.Thool “Automatic Facial Feature Extraction and Expression Recognition based on Neural Network” (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No.1.

• In 2012, Dilbag Singh “Human Emotion Recognition System” Guru Nanak Dev University Amritsar (Punjab) India , I.J. Image, Graphics and Signal Processing, 8, 50-56.

Related works

• 2013 , Jeemoni Kalita , Karen Das “Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique” (IJACSA).

• March 2015 , Shail Kumari Shah , Vineet Khanna “ Facial Expression Recognition for Color Images using Gabor, Log Gabor Filters and PCA” International Journal of Computer Applications (0975 – 8887) Volume 113 – No. 4.

Basic Structure of Facial Expression analysis

Generic facial expression analysis framework

The proposed system

• We are trying to design a system able to identify for basic 6 facial Expression efficient and accurate depending on the improvement in the extraction of features which represents the core of the system .

• programming language “MatLab R2013a” Or newer

Conclusion

• The objective of this PPT is to show a clean survey on the structure of analyzing the facial expression . The steps involved in expression analysis like face acquisition, feature extraction and expression classification had been discussed.

• In addition to some of the challenges facing research in general.

References

• P. Ekman, E. R. Sorenson, and W. V. Friesen, “Pan cultural elements in Facial displays of emotion” Science, New Series, vol. 164, no. 3875, pp. 86-88, April 4,1969.

• G. R. S. Murthy and R. S. Jadon, “Effectiveness of Eigenspaces for Facial Expressions Recognition” International Journal of Computer Theory and Engineering, vol. 1, no. 5, pp. 638-642, December 2009.

• B. Fasela , Juergen Luettinb , “Automatic facial expression analysis: a survey” – Pattern Recognition 36 (2003) 259 – 275 .

• C.P. Sumathi, T. Santhanam and M.Mahadevi ,International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.6, December 2012 (AUTOMATIC FACIAL EXPRESSION ANALYSIS :A SURVEY )