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Human emotion recognition from face ...

Dutta, Paramartha.

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Human emotion recognition from face images

Record Type:	Electronic resources : Monograph/item
Title/Author:	Human emotion recognition from face images/ by Paramartha Dutta, Asit Barman.
Author:	Dutta, Paramartha.
other author:	Barman, Asit.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xix, 264 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Distance Signature for Recognizing Human Emotions -- Shape Signature for recognizing Human Emotion -- Distance Shape Signature Duo Ford Determination of Human Emotion -- Distance Texture Signature Duo for Determination of Human Emotion.
Contained By:	Springer eBooks
Subject:	Human face recognition (Computer science) -
Online resource:	https://doi.org/10.1007/978-981-15-3883-4
ISBN:	9789811538834

Human emotion recognition from face images
Dutta, Paramartha.

Human emotion recognition from face images[electronic resource] /by Paramartha Dutta, Asit Barman. - Singapore :Springer Singapore :2020. - xix, 264 p. :ill., digital ;24 cm. - Cognitive intelligence and robotics,2520-1956. - Cognitive intelligence and robotics..

Introduction -- Distance Signature for Recognizing Human Emotions -- Shape Signature for recognizing Human Emotion -- Distance Shape Signature Duo Ford Determination of Human Emotion -- Distance Texture Signature Duo for Determination of Human Emotion.

This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition. The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas.

ISBN: 9789811538834

Standard No.: 10.1007/978-981-15-3883-4doiSubjects--Topical Terms:

704445
Human face recognition (Computer science)

LC Class. No.: TA1653 / .D87 2020

Dewey Class. No.: 006.4

Human emotion recognition from face images
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100 1 $a Dutta, Paramartha. $3 2179172
245 1 0 $a Human emotion recognition from face images $h [electronic resource] / $c by Paramartha Dutta, Asit Barman.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xix, 264 p. : $b ill., digital ; $c 24 cm.
490 1 $a Cognitive intelligence and robotics, $x 2520-1956
505 0 $a Introduction -- Distance Signature for Recognizing Human Emotions -- Shape Signature for recognizing Human Emotion -- Distance Shape Signature Duo Ford Determination of Human Emotion -- Distance Texture Signature Duo for Determination of Human Emotion.
520 $a This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition. The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas.
650 0 $a Human face recognition (Computer science) $3 704445
650 0 $a Emotion recognition $x Computer programs. $3 3449591
650 1 4 $a User Interfaces and Human Computer Interaction. $3 892554
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Pattern Recognition. $3 891045
700 1 $a Barman, Asit. $3 3449590
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Cognitive intelligence and robotics. $3 3338190
856 4 0 $u https://doi.org/10.1007/978-981-15-3883-4
950 $a Computer Science (Springer-11645)