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面向人機(jī)交互的人臉表情識別技術(shù)(英文版)

面向人機(jī)交互的人臉表情識別技術(shù)(英文版)

定 價:¥98.00

作 者: 宋斌,張志勇
出版社: 科學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 暫缺

ISBN: 9787030674661 出版時間: 2022-06-01 包裝:
開本: 16開 頁數(shù): 157 字?jǐn)?shù):  

內(nèi)容簡介

  《面向人機(jī)交互的人臉表情識別技術(shù)=Facial Expression RecognitionTechnology for Human-Computer Interaction:英文》根據(jù)工程應(yīng)用的實(shí)際需要,全面系統(tǒng)地介紹了面向人機(jī)交互的人臉表情識別技術(shù),主要內(nèi)容包括:根據(jù)視覺信息處理的分模塊性原理,對彩色圖像的恒常性問題進(jìn)行研究,解決傳統(tǒng)顏色恒常性的不適定問題;為實(shí)現(xiàn)高效準(zhǔn)確的人臉檢測和面部特征定位,對多特征融合的人臉檢測方法和面部特征點(diǎn)定位問題進(jìn)行研究;綜合考慮人臉表情特征的重要性和提取的有效性,對表情特征提取方法進(jìn)行研究;考慮融入表情樣本的類別信息,對有監(jiān)督的正交保局投影的表情識別算法進(jìn)行研究。

作者簡介

暫缺《面向人機(jī)交互的人臉表情識別技術(shù)(英文版)》作者簡介

圖書目錄

Contents \n
Preface \n
Chapter 1 Introduction 1 \n
1.1 Research Background and Significance 1 \n
1.2 Overview of Facial Expression Recognition 4 \n
1.3 Research Status at Home and Abroad 7 \n
1.3.1 Typical Facial Expression Recognition Algorithms 7 \n
1.3.2 Existing Problems in Facial Expression Recognition 13 \n
1.4 Research Contents 14 \n
Chapter 2 Color Constancy Algorithm for Color Image Under Complex Illumination Conditions 20 \n
2.1 Introduction 20 \n
2.2 Correction of Color Deviation 21 \n
2.2.1 LoG Chrominance Edge Extraction 23 \n
2.2.2 White Balance Adjustment 28 \n
2.2.3 Experimental Results and Analysis 30 \n
2.3 Luminance Enhancement 32 \n
2.3.1 Retinex Enhancement Algorithm 32 \n
2.3.2 Color Retention Enhancement Algorithm 35 \n
2.3.3 Experimental Results and Analysis 40 \n
2.4 Fractional Step Color Constancy Algorithm 42 \n
2.5 Summary of This Chapter 45 \n
Chapter 3 Face Detection Algorithm with Multi-feature Fusion 46 \n
3.1 Introduction 46 \n
3.2 Skin Color Area Detection 49 \n
3.2.1 Common Color Space 49 \n
3.2.2 Skin Color Clustering Analysis 55 \n
3.2.3 Skin Color Area Detection Algorithm 57 \n
3.3 AdaBoost Face Detection Combined with Skin Color Features 60 \n
3.3.1 AdaBoost Algorithm 62 \n
3.3.2 AdaBoost Face Detection Algorithm Combined with Skin Color Features 67 \n
3.4 Face Authentication Based on Harris Corner Point Detection 69 \n
3.4.1 Principles for Harris Corner Point Detection 69 \n
3.4.2 Harris Corner Point Detection Algorithm 71 \n
3.4.3 Face Authentication Based on Harris Corner Point Detection 73 \n
3.5 Experimental Results and Analysis 74 \n
3.6 Summary of This Chapter 76 \n
Chapter 4 Facial Features Location 78 \n
4.1 Introduction 78 \n
4.2 Eye Location Based on the Robustness of Illuminated Expression 79 \n
4.2.1 Multi-scale Self-quotient Image 80 \n
4.2.2 Rough Location of Morphological Filtering 81 \n
4.2.3 Precise Eye Location 85 \n
4.2.4 Experimental Results and Analysis 86 \n
4.3 Location System of Key Color Facial Feature Point 90 \n
4.3.1 Overview of the System 90 \n
4.3.2 Eyes Location 92 \n
4.3.3 Mouth Location 95 \n
4.3.4 Experimental Results and Analysis 97 \n
4.4 Summary of This Chapter 99 \n
Chapter 5 Normalization of Facial Expression Image 101 \n
5.1 Introduction 101 \n
5.2 Rotation Normalization 102 \n
5.3 Size Normalization 104 \n
5.4 Illumination Normalization 106 \n
5.5 Experimental Results and Analysis 110 \n
5.6 Summary of This Chapter 111 \n
Chapter 6 Extraction of Facial Expression Features 112 \n
6.1 Introduction 112 \n
6.2 Gabor Local Statistical Features 116 \n
6.3 LBP Features 120 \n
6.3.1 Basic LBP and Its Improvement 120 \n
6.3.2 Uniform LBP Algorithm 122 \n
6.3.3 Expression Features Extracted by LBP Histogram 124 \n
6.4 Summary of This Chapter 125 \n
Chapter 7 Facial Expression Recognition Based on Supervised Orthogonal Locality Preserving Projection 127 \n
7.1 Introduction 127 \n
7.2 LPP Algorithm 129 \n
7.2.1 Laplacianface Algorithm 129 \n
7.2.2 Orthogonal Laplacianface Algorithm 133 \n
7.3 Expression Recognition with SOLPP 135 \n
7.3.1 LDA 135 \n
7.3.2 SOLPP 136 \n
7.3.3 Classification of Facial Expressions 140 \n
7.4 Experimental Results and Analysis 141 \n
7.5 Summary of This Chapter 147 \n
Chapter 8 Conclusion and Future Works 148 \n
8.1 Conclusion 148 \n
8.2 Future Works 150 \n
References 153

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