FACIAL EXPRESSION ANALYSIS FROM 3D RANGE IMAGES; COMPARISON WITH THE ANALYSIS FROM 2D IMAGES AND THEIR INTEGRATION

机译：3D范围图像的面部表达分析;与2D图像分析及其集成的分析比较

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Even if facial expression analysis from 2D luminance images is the present mainstream, it has problems due to changes in facial pose and lighting. In this paper, we use 3D range images which do not maintain such problems for facial expression analysis. We first apply the subspace method to range and luminance images, and clarify their differences in image characteristics. Examining the validity of range images for facial expression analysis, we consider improvement in correct classification rates by integrating results from range and luminance images. We employ the linear combination for their integration and show experimental results.

机译：即使来自2D亮度图像的面部表达分析是当前主流，它也存在由于面部姿势和照明的变化而存在问题。在本文中，我们使用3D范围图像，该图像不会在面部表达分析中维持这些问题。我们首先将子空间方法应用于范围和亮度图像，并阐明它们在图像特征中的差异。检查范围图像的有效性进行面部表情分析，我们考虑通过集成范围和亮度图像的结果来改进正确的分类率。我们采用线性组合进行整合并显示实验结果。

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《IEEE International Conference on Image Processing》|2003年||共4页
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T. Yabui; Y. Kenmochi; K.kotani;
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中图分类 TN911.73-53;
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1. Analysis of Range Images Used in 3D Facial Expression Recognition Systems [J] . Xiaoli, Ruan, Qiuqi, Computing and informatics . 2016,第1期

机译：3D面部表情识别系统中使用的距离图像分析
2. ANALYSIS OF RANGE IMAGES USED IN 3D FACIAL EXPRESSION RECOGNITION SYSTEMS [J] . Li Xiaoli, Ruan Qiuqi, An Gaoyun, Computing and informatics . 2016,第1期

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3. Deep Learning Based Classification of 2D and 3D Images For Facial Expression Recognition: Comparison Study [J] . Fouzia Adjailia, Diana Olejarova, Peter Sincak Computer Science & Information Technology . 2020,第10期

机译：面部表情识别2D和3D图像的深度学习分类：比较研究
4. FACIAL EXPRESSION ANALYSIS FROM 3D RANGE IMAGES; COMPARISON WITH THE ANALYSIS FROM 2D IMAGES AND THEIR INTEGRATION [C] . T. Yabui, Y. Kenmochi, K.kotani IEEE International Conference on Image Processing . 2003

机译：3D范围图像的面部表达分析;与2D图像分析及其集成的分析比较
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FACIAL EXPRESSION ANALYSIS FROM 3D RANGE IMAGES; COMPARISON WITH THE ANALYSIS FROM 2D IMAGES AND THEIR INTEGRATION

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