Mohammed Abdul Rahman
College of Science
Department of Computer Science
Under the supervision
d. Zainab Ibrahim
• The aim of research
• History (Introduction & Previous Works)
• Importance of research and its Applications
• Physically analysis
• Related works
• Basic Structure of Facial Expression analysis
• The proposed system
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
• 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.
• In recent years, a lot of work has been done
on the affective recognition of expressions
which holds the major key in the human-
• 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.
• 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,
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.
• The movement of facial muscles areas
• 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… ?
• The main challenges in automatic affect
• Head-pose variations.
• illumination variations.
• Registration errors.
• 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.
• 2013 , Jeemoni Kalita , Karen Das “Recognition of Facial
Expression Using Eigenvector Based Distributed Features
and Euclidean Distance Based Decision Making Technique”
• 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.
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
• 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
• In addition to some of the challenges facing
research in general.
• 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 )