DETECTING FACIAL EXPRESSION IN IMAGES

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Journal for Research | Volume 02 | Issue 02 | April 2016 ISSN: 2395-7549

Detecting Facial Expression in Images Ghazaala Yasmin M.Tech. Student Department of Computer Science & Engineering University of Calcutta

Prof. Samir K. Bandyopadhyay Professor Department of Computer Science & Engineering University of Calcutta

Abstract Now days, the task of face recognition is widely used application of image analysis as well as pattern recognition. In biometric area of the research, automatically face & face expression recognition attracts researcher’s interest. For classifying facial expressions into different categories, it is necessary to extract important facial features which contribute in identifying proper and particular expressions. Recognition and classification of human facial expression by computer is an important issue to develop automatic facial expression recognition system in vision community. In this paper the facial expression recognition system is proposed. Keywords: Facial feature detection, Template matching and Face position detection _______________________________________________________________________________________________________ I.

INTRODUCTION

Facial expression recognition [1] [2] is another fruitfulness of computer vision research. Computer vision is the way to electronically represent the human vision with the help of some data analysis techniques. In a human computer interaction (HCI) system, the communication between human and computer can take place through different aspects (like verbal, non-verbal) of a human. Here we are considering only the non-verbal aspects of human being like, facial expression, body movement etc. In this paper we are mainly concern about the facial expression recognition process, which needs a face image on which we should apply our facial expression recognition algorithm. Now once we have the face image data, we need to apply some processing techniques with the help of pattern recognition, artificial intelligence, mathematics, computer science, electronics or any kind of scientific concept. Hence there are huge numbers of applications in computer vision research, but we will discuss only face recognition and facial expression. There are many applications, where facial expression detection process plays an important role. Researches in the field of social psychology show that facial expression are more natural in nature than the speaker’s spoken words and truly reflects the emotion of a person. According to statistical reports verbal part of a message contributes only for 7 percent to the effect of the message as a whole. The vocal part contributes for 38 percent, while facial expression of the speaker contributes for 55 percent to the effect of the spoken message. The facial expression recognition system was introduced in 1978 by Suwa et. al [4]. The main issue of building a facial expression recognition system is face detection [3] and alignment, image normalization, feature extraction, and classification. The analysis of the human face via image (and video) is one of the most interesting and focusing research topics in the last years for the image community. From the analysis (sensing, computing, and perception) of face images, much information can be extracted, such as the sex/gender, age, facial expression, emotion/temper, mentality/mental processes and behaviour/psychology, and the health of the person captured. According to this information, many practical tasks can be performed and completed; these include not only person identification or verification (face recognition), but also the estimation and/or determination of person's profession, hobby, name (recovered from memory), etc. Research on face image analysis has been carried out and is being conducted around various application topics, such as (in alphabetical order) age estimation, biometrics, biomedical instrumentations, emotion assessment, face recognition, facial expression classification, gender determination, human-computer/human-machine interaction, human behaviour and emotion study, industrial automation, military service, psychosis judgment, security checking systems, social signal processing, surveillance systems, sport training, tele-medicine service, etc. Therefore facial expressions are the most important information for emotions perception in face to face communication. This paper explains about an approach to the problem of facial feature extraction from a non-l frontal posed image For face portion segmentation basic image processing operation like morphological dilation, erosion, reconstruction techniques with disk structuring element are used. Six permanent Facial features like eyebrows(left and right), eye (left and right) , mouth and nose are extracted using facial geometry, edge projection analysis and distance measure and feature vector is formed considering height and width of left eye, height and width of left eyebrow, height and width of right eye, height and width of right eyebrow, height and width of nose and height and width of mouth along with distance between left eye and eyebrow, distance between right eye and eyebrow and distance between nose and mouth. Human face detection has drawn considerable attention in the past decades as it is one of the fundamental problems in computer vision. Given a single image, the ideal face detection should identify and locate all faces regardless of its threedimensional position, orientation, and lighting conditions. The existing face detection techniques can be classified into four

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