Facial Emotion Recognition using LBP and SVM Technique

Registration ID: IJNRD_180037

Published ID: IJNRD1803012

DOI: Click Here to Get

Shubham Meshram , Shashipal Panwar , Mustak Soloanki , Akshay Waghmare , Prof. Muzzafar Khan

Facial,Emotiong,LBP,SVM,Jaffe Database.

Facial expressions convey non-verbal cues, which play an important role in interpersonal relations. Automatic recognition of facial expressions can be an important component of natural human-machine interfaces; it may also be used in behavioural science and in clinical practice. Automatic facial expression recognition system has many applications including, but not limited to, human behavior understanding, detection of mental disorders, and synthetic human expressions. Two popular methods utilized mostly in the literature for the automatic FER systems are based on geometry and appearance. Even though there is lots of research using static images, the research is still going on for the development of new methods which would be quiet easy in computation and would have less memory usage as compared to previous methods. This paper presents a quick survey of facial expression recognition. A comparative study is also carried out using various feature extraction techniques on JAFFE dataset. Support Vector Machine (SVM) is used as a classifier for classifying the expressions of supplied face into five basic expressions like surprise, neutral, sad,happy and angry.

Published Paper   E-Certificate

Shubham Meshram, Shashipal Panwar, Mustak Soloanki, Akshay Waghmare, & Prof. Muzzafar Khan (March-2018). Facial Emotion Recognition using LBP and SVM Technique . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 3(3), 52-55. https://ijnrd.org/papers/IJNRD1803012.pdf

Volume 3 Issue 3, March-2018

Pages : 52-55

Paper Reg. ID: IJNRD_180037

Published Paper Id: IJNRD1803012

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Research Area: Engineering

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Published Paper PDF: https://ijnrd.org/papers/IJNRD1803012.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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