Emotion Recognition Based on Efficient Self Organized Map

Page 1

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 04 | Apr -2017

www.irjet.net

p-ISSN: 2395-0072

Emotion Recognition Based on Efficient Self Organized Map Harshada Sonkamble1 Prof. Ujwala.V. Gaikwad2 Terna Engineering College, Nerul ------------------------------------------------------------------------------------------------------------------------------------------emotions

Abstract- The face being the primary focus of

in

order

to

enhance

productivity

and

effectiveness of working with computers.

attention in social interaction plays a major role in

Nowadays,

Emotion

recognition

is

well

conveying identity and emotion. The emotion recognition

recognized desired features of Intelligent Tutoring

system is a computer application for automatically

Systems, with primary focus on such learner dullness,

identifying a person and its emotion from digital images or

frustration. An emotion recognition system also used for

video frame from a video source.

driver stress testing and psychological diseases [1].

The

proposed

automatic

facial

expression

The human-computer interaction (HCI) will be

recognition system can detect human face, extract facial

much more effective if a computer is able to recognize the

features, and recognize facial emotions. The inputs to the

emotion of the human, which can say about the mood of

proposed system are a sequence of images, still images or

the person. The objective of automatic facial emotion

webcam images. An input of modified self-organizing map

recognition system is to take human facial images

(SOM) is a facial geometric feature including eye, lip and

containing some expression as input and recognize and

eyebrow feature points.

classify it into appropriate expression classes such as

This system is very efficient in recognizing six basic emotions.

angry, disgust, fear, happy, sad, and surprise. Automatic facial emotion recognition systems

Keywords— facial Expression, geometric facial feature, feature

extraction,

self-organized

map,

have been used in applications like human robot

Emotion

interactions, human-computer interactions, virtual reality,

Recognition.

etc. In this human facial expressions play an important role. Six basic expressions are happiness, sadness,

1. INTRODUCTION

surprise; fear, anger, and disgust have been considered by Ekman [2].

The human face plays an important role in verbal and

non-verbal

communication.

verbal

The automatic facial expression recognition

communication, the face is involved in speech and as far as

problem is a very challenging problem because it involves

non-verbal

in three sub-problems:

communication

is

Regarding

concerned,

the

face

1.1 Face Detection

communicates through expression of emotions and gestures such as nods and winks. Affective computing is a

Face Detection is the process of locating and

domain that focuses on user emotions while interacting

extracting the face region from the images. It involves

with computers and applications. The mind of a person

segmentation, extraction, and verification of faces. It

may influence concentration, skills of decision making,

follows two different approaches: Face detection from still

and solving the different tasks. Affective computing vision

images and Face detection from images acquired from a

is to make systems able to recognize and influence human

video.

Š 2017, IRJET

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