Facial Expression Recognition using Knn Classifier

Language: English

Published by LAP LAMBERT Academic Publishing, 2020

6202525274 / 9786202525275

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nach der Bestellung gedruckt Neuware - Printed after ordering - The comparison between the methodologies used for human emotion recognition from face images based on textural analysis and KNN clas- sifier. Automatic facial expression recognition (FER) plays an impor- tant role in Human Computer Interaction (HCI) systems for measuring people's emotions has dominated psychology by linking expressions to a group of basic emotions (i.e., anger, disgust, fear, happiness, sad- ness, and surprise).The comparative study of Facial Expression Recog- nition involves Curvelet transform based Robust Local Binary Pattern (RLBP) and Distinct LBP (DLBP) features and features derived from DLBP and GLCM. The objective of this research is to show that fea- tures derived from RLBP with DLBP is superior to the features de- rived from DLBP and GLCM. To test and evaluate their performance, experiments are performed using Japanese Female Expressions Model (JAFEE) database in both techniques. The comparison chart shows that, the DLBP and RLBP based feature extraction with KNN classi- fier gives much better accuracy than other existing methods.

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Title
Facial Expression Recognition using Knn Classifier
Author
Shailendra Pardeshi
Publisher
LAP LAMBERT Academic Publishing
Publication year
2020
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6202525274
ISBN 13
9786202525275
Item weight
96 grams
Dimensions
220x150x4 mm

AHA-BUCH GmbH

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