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首页> 外文会议>European Conference on Computer Vision(ECCV 2006) Workshop on Human-Computer Interaction(HCI); 20060513; Graz(AT) >EigenExpress Approach in Recognition of Facial Expression Using GPU
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EigenExpress Approach in Recognition of Facial Expression Using GPU

机译：EigenExpress方法使用GPU识别面部表情

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摘要

The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. In this paper, a novel system is proposed to recognize human facial expressions based on the expression sketch. Firstly, facial expression sketch is extracted by an GPU-based real-time edge detection and sharpening algorithm from original gray image. Then, a statistical method, which is called Eigenexpress, is introduced to obtain the expression feature vectors for sketches. Finally, Modified Haus-dorff distance(MHD) was used to perform the expression classification. In contrast to performing feature vector extraction from the gray image directly, the sketch based expression recognition reduces the feature vector's dimension first, which leads to a concise representation of the facial expression. Experiment shows our method is appreciable and convincible.
机译：面部表情的自动识别给模式分析和人机交互研究界提出了重大挑战。本文提出了一种基于表情草图的人脸表情识别系统。首先，通过基于GPU的实时边缘检测和锐化算法从原始灰度图像中提取面部表情草图。然后，引入一种称为Eigenexpress的统计方法，以获取草图的表达特征向量。最后，使用修正的Haus-dorff距离（MHD）进行表情分类。与直接从灰度图像中提取特征向量相比，基于草图的表情识别首先会减小特征向量的维数，从而使人脸表情更加简洁。实验表明，我们的方法是合理的和令人信服的。

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