Classification of Human Facial Expression: | An Application of Image Processing and Machine Learning

Sohail Abu Sayeed Md.

ISBN 10: 3639068637 / ISBN 13: 9783639068634

Published by VDM Verlag Dr. Müller, 2013

About this Item

Classification of Human Facial Expression: | An Application of Image Processing and Machine Learning | Sohail Abu Sayeed Md. | Taschenbuch | Kartoniert / Broschiert | Englisch | 2013 | VDM Verlag Dr. Müller | EAN 9783639068634 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.

Seller Inventory # 101746448

Bibliographic Details

• Title: Classification of Human Facial Expression: | An Application of Image Processing and Machine Learning
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2013
• Language: English
• ISBN 10: 3639068637
• ISBN 13: 9783639068634
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 11W x 150H x 220D millimeters 11 millimeters width by 150 millimeters height by 220 millimeters depth
• Weight: 284 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book describes a computer vision system fordetection and classification of 7 basic facialexpressions. Facial expressions are communicated bysubtle changes in one or more discrete features suchas tightening the lips, raising the eyebrows, openingand closing of eyes or certain combination of them,which can be identified through monitoring thechanges in muscles movements located around the aboveregions. In our research, an analytic facerepresentation consists of 15 feature points has beenused that identifies the principle muscle actions andprovides visual observation of the discrete featuresresponsible for each of the 7 basic emotions. Featurepoints from the region of mouth have been detected bysegmenting the lip contour applying a variationalformulation of the level set method. A multi-detectorapproach of facial feature point detection has beenutilized for identifying the points of interest fromthe region of eye, eyebrow and nose. Feature vectorscomposed of 15 features are then obtained from thesefeature points and used to train a SVM classifier sothat the system can classify facial expressions froman unknown face image with a certain level of accuracy.

About the Author

Abu Sayeed Md. Sohail received Master’s in Computer Science fromConcordia University, Canada in August 2007. Presently he isworking there as a Ph.D. researcher. He has over 20 researchpublications in the area of Computer Vision. His researchinterest includes Computer Analysis of Facial Expressions, Designof Multimodal Human-Computer Interface.