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Human emotion recognition from face ...
~
Dutta, Paramartha.
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Human emotion recognition from face images
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Human emotion recognition from face images/ by Paramartha Dutta, Asit Barman.
作者:
Dutta, Paramartha.
其他作者:
Barman, Asit.
出版者:
Singapore :Springer Singapore : : 2020.,
面頁冊數:
xix, 264 p. :ill., digital ;24 cm.
內容註:
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
標題:
Human face recognition (Computer science) -
電子資源:
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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