LastBSCS FINAL PROJECT PROPOSAL(ER) SRS1 Correction.docx

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BSCS FINAL PROJECT PROPOSAL

Emotion Recognition by Facial

Expressions

Term: Spring 2013

Presented by:

Registration No: Name:L1F09BSCS2090 HASSAN SHABBIR

L1F09BSCS2019 WALEED KHALID

Faculty of Information Technology

University of Central Punjab



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Project Title

Emotion Recognition by Facial Expressions

Project Advisor Prof. Yasir Danial Khan

Particulars of the students:

S.No Registration#eg.L1F00MSCS0101

Name in FullUse Block Letters

CGPA Signatures

1 L1F09BSCS2090 HASSAN SHABBIR 2.49

2 L1F09BSCS2019 WALEED KHALID 2.23

Advisor’s Consent I Prof./Dr./Mr./Ms. ________________________________________________ am willing to

guide these students in all phases of above-mentioned project / thesis as advisor. I have

carefully seen the Title and description of the project / thesis and believe that it is of an

appropriate difficulty level for the number of students named above.

Note: Advisor can’t be changed without priorpermission of the

Manager Projects and the duration for completion of

Research Project / Thesis is 1 Year (approx.) from the date of

Registration of Research Project/Thesis.

Signatures and Date

Advisor

REFERENCE 1I have carefully read the project proposal and feel that the proposed project is a useful one

and of a sufficient difficulty level to justify a one year work load of above mentioned students.

Recommended Signatures and Date

Yes No

REFERENCE 2I have carefully read the project proposal and feel that the proposed project is a useful one

and of a sufficient difficulty level to justify a one year work load of above mentioned students.

Recommended Signatures and Date

Yes No



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Signature Reference – 1 Signature Reference – 2

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Abstract

Emotions play a vital role in people’s everyday life. It is a mental state that does not

arise through free will and is often accompanied by physiological changes. Therefore

monitoring these changes is important as they are perceptions of emotional changes

and can help in identifying matters of concern at an early stage before they becomeserious. Emotion recognition has become an important subject when it comes to

human-machine interaction. Various methods have been used in past to detect and

evaluate human emotions. The most commonly used techniques include the use of

textual information, speech, body gestures and physiological signals. In this project

we will develop an emotion recognition system based on information provided by the

facial expressions. The four basic emotions observed in this project are happy

(excited), sad, angry and neutral (relaxed). The data has been collected from healthy

individuals, including both male and female. [1][2]

Clear Statement of the Problem

It is proposed to design a real time monitoring systems, capable of evaluating four

basic emotions i.e. happy, sad, angry and neutral. In order to introduce affect

recognition and its possible applications to the information security community. The

implementation of these systems will represent the realization of an important goal for

the security industry, the automation of real-time prediction of human behavior and

intention. [2] If any company makes a funny/sad advertisement and they are not sure

their advertisement is up to the mark. The implementation of these systems will help

them to find out their advertisement is ready or not for market arranging test run by

showing their advertisement to different sets of people.Objectives

As we know, computers and robots are being used widely for betterment of our daily

life therefore it is important for computers and robots to have an artificial mind that

would enable them to communicate with human beings using both logical and

emotional information and our main objective of this project is to design a real time

monitoring systems, capable of evaluating four basic emotions i.e. happy, sad, angry

and neutral.[2] The basic idea of emotion recognition using facial expression is to

segment facial images into various regions of interest. The common regions taken into

account include movements of cheeks, chin, eyes, eyebrows, and mouth. Different

Classification techniques are then applied to differentiate between types of emotions.

Motivation

Over the past decades, human-computer interaction with computer vision has been an

important field in computer study. It is concerned with the relationship of direct

communication between the computer and human beings. Much research has been

conducted on improving and developing the interaction between humans and the

computer. Interested researchers worked on this area for different reasons. One of the

significant factors that contributed to increasing and developing the interaction between

the computer and humans is studying the computer's ability to distinguish emotions for



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humans and the motivation for this project has stemmed from numerous sources.

Firstly the desire is to work and create content with Image Processing and secondly I

always have been keen to do things that are new, and push technology to set new

foundations.

I want to bring IP social interactions together to create a much more appealing andinteractive social medium.

Sometimes we are unable to find out the proper mood of the person during simple

chat where cam is not available this thing will help to find out the mood by changing

the background or sending the emotions automatically. (If angry backgrounds will be

red). This software will help others software as well.

Introduction and Background

Facial emotion recognition plays a vital role when it comes to developing multi-

cultural visual communication systems for emotion translation between cultures. As

we know computers and robots are being used widely for betterment of our daily life

therefore it is important for computers and robots to have an artificial mind that would

enable them to communicate with human beings using both logical and emotional

information The basic idea of emotion recognition using facial expression is to

segment facial images into various regions of interest. The common regions taken into

account include movements of cheek, chin, wrinkles, eyes, eyebrows, and mouth.

Different classification techniques are then applied to differentiate between different

types of emotions. The analysis and evaluation of facial expressions. The proposedscheme used external stimulus to excite specific emotions in human subjects whose

facial expressions were analyzed by segmenting and localizing the individual frames

into regions of interest. Selected facial features such as eye opening, mouth opening.

The system is developed to analyze the test data based on the provided training data to

recognize the emotional states. Our System should recognize seven emotions – anger,

contempt, disgust, fear, joy, sadness, and surprise and also be able to detect emotions

from video, image or real time facial expression.

When we smile, frown or grimace, thousands of tiny facial muscles are at work.

Emotion-recognition software, or ERS, creates a 3-D face map, pinpointing trigger

areas like eye and mouth corners.

Then a face-tracking algorithm matches the movements to basic expression patterns,

corresponding to anger, sadness, fear, surprise, disgust and happiness, or a mixture of

them. [3]



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Related Work

There is a vast body of literature on emotion. Emotion recognition has been

investigated with the Speech and body gesture but the results are generally obtained

with acted emotion database because they contain strong emotional expressions.Recent discoveries suggests that emotions are intricately linked to other functions

Such as attention, perception, memory, decision making, and learning. In this, we

concentrate on the expressive nature of emotion, especially those expressed on the

face.

Project Plan / Schedule



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Resources Required

1) Internet Connectivity

2) Pc

3) Web cam

References

[1] M.Tauseef Quazi, Emotion recognition by using smart sensor

ACM Digital Library, School of engineering and technology, Massey University,

New Zealand, pp. 5-10, Feb 2012

[2]: ACM Joseph Burlington, Proceedings of the 2nd annual conference on

Information security curriculum development, Georgia Southern University,

Statesboro, GA, New York, USA, Pages 95-99, 2005

[3]: Nicole Martinelli, Emotion-Recognition Knows What Makes YouSmile, University, Statesboro, GA, New York, USA, Pages 40-41-, 2007

[4] M. T. Quazi, “Human Emotion Recognition Using Smart Sensors”,

Electronics, Information and Communication System (EICS) Seminar, 21st March2011. Massey University, Palmerston North, New Zealand

LastBSCS FINAL PROJECT PROPOSAL(ER) SRS1 Correction.docx

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