Facial Expression Identification using Regularized Supervised Distance Preserving Projection

S. Jahan, Moriyam Akter, Sifta Yeasmin, Farhana Ahmed Simi
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Abstract

Facial expression recognition is one of the most reliable and a key technology of advanced human-computer interaction with the rapid development of computer vision and artificial intelligence. Nowadays, there has been a growing interest in improving expression recognition techniques. In most of the cases, automatic recognition system’s efficiency depends on the represented facial expression feature. Even the best classifier may fail to achieve a good recognition rate if inadequate features are provided. Therefore, feature extraction is a crucial step of the facial expression recognition process. In this paper, we have used Regularized Supervised Distance Preserving Projection for extracting the best features of the images. Numerical experiment shows that the use of this technique outperforms many of state of art approaches in terms of recognition rate. Dhaka Univ. J. Sci. 69(2): 70-75, 2021 (July)
基于正则化监督距离保持投影的面部表情识别
随着计算机视觉和人工智能的迅速发展,面部表情识别是先进人机交互技术中最可靠的关键技术之一。目前,人们对改进表情识别技术的兴趣越来越大。在大多数情况下,自动识别系统的效率取决于所代表的面部表情特征。如果提供的特征不充分,即使是最好的分类器也可能无法达到良好的识别率。因此,特征提取是人脸表情识别过程中至关重要的一步。在本文中,我们使用正则化监督距离保持投影来提取图像的最佳特征。数值实验表明,该方法在识别率方面优于许多现有方法。达卡大学学报(自然科学版),69(2):70-75,2021 (7)
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