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Titlebook: Computational Techniques for Human Smile Analysis; Hassan Ugail,Ahmad Ali Asad Aldahoud Book 2019 The Author(s), under exclusive license t

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發(fā)表于 2025-3-21 18:30:47 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computational Techniques for Human Smile Analysis
編輯Hassan Ugail,Ahmad Ali Asad Aldahoud
視頻videohttp://file.papertrans.cn/234/233179/233179.mp4
概述Explains how to implement computational techniques for human smile analysis.Shares insights into the human personality traits hidden in a smile.Enriches the understanding of human emotions through exa
叢書(shū)名稱SpringerBriefs in Computer Science
圖書(shū)封面Titlebook: Computational Techniques for Human Smile Analysis;  Hassan Ugail,Ahmad Ali Asad Aldahoud Book 2019 The Author(s), under exclusive license t
描述..In this book, the authors discuss the recent developments in computational techniques for automated non-invasive facial emotion detection and analysis with particular focus on the smile. By way of applications, they discuss how genuine and non-genuine smiles can be inferred, how gender is encoded in a smile and how it is possible to use the dynamics of a smile itself as a biometric feature...It is often said that the face is a window to the soul. Bearing a metaphor of this nature in mind, one might find it intriguing to understand, if any, how the physical, behavioural as well as emotional characteristics of a person could be decoded from the face itself. With the increasing deductive power of machine learning techniques, it is becoming plausible to address such questions through the development of appropriate computational frameworks. Though there are as many as over twenty five categories of emotions one could express, regardless of the ethnicity, gender or social class, across humanity, there exist six common emotions – namely happiness, sadness, surprise, fear, anger and disgust - all of which can be inferred from facial expressions. Of these facial expressions, the smile is
出版日期Book 2019
關(guān)鍵詞Face Analysis; Smile Analysis; Computational Methods; Smile Dynamics; Machine Learning; Facial Emotion An
版次1
doihttps://doi.org/10.1007/978-3-030-15381-6
isbn_softcover978-3-030-15380-9
isbn_ebook978-3-030-15381-6Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2019
The information of publication is updating

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A Computational Framework for Measuring the Facial Emotional Expressions,ch here is to identify the face and estimate regions of facial features of interest using the optical flow algorithm. Once the regions and their dynamics are computed a rule based system can be utilised for classification. Using this framework, we show how it is possible to accurately identify and c
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Gender and Smile Dynamics,s of a smile. The computational smile dynamics framework we discuss here uses the spatio-temporal changes on the face during a smile. Specifically, it uses a set of spatial and temporal features on the overall face. These include the changes in the area of the mouth, the geometric flow around facial
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Introduction: Altitudes of Authority, features and a set of intrinsic features over the face. These features are explicitly derived from the dynamics of the smile. Based on it, a number of distinct dynamic smile parameters can be extracted which can then be fed to a machine learning algorithm for gender classification.
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