RETRACTED ARTICLE: Expression recognition algorithm based on MDS-HOG feature optimization and differential weights

Kelei Sun (), Mengqi He, Daoyi Zhang and Huaping Zhou ()
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Kelei Sun: Anhui University of Science and Technology
Mengqi He: Anhui University of Science and Technology
Daoyi Zhang: Anhui University of Science and Technology
Huaping Zhou: Anhui University of Science and Technology

Journal of Combinatorial Optimization, 2023, vol. 45, issue 1, No 9, 17 pages

Abstract: Abstract Facial expression recognition methods based on convolutional neural networks have greatly improved the recognition accuracy. However, the feature information of face images has not been fully extracted in these methods, which are mainly due to insufficient features of facial expressions in some Key positions, such as eyes, nose, and mouth. Adjusting the weights of these key positions can improve the accuracy of facial expression recognition. To address this problem, we propose a differential weight-based multi-dimension and multi-scale HOG algorithm (MDS-HOG). It can extract various types of deep features, thus enriching facial expression feature information. First, facial expression data is preprocessed using ENM region acquisition. Then, on the basis of the original HOG algorithm, the diagonal gradient information of the image is added to obtain the multi-dimension HOG feature. Furthermore, a multi-scale spatial pyramid is constructed to extract multi-scale HOG features. Finally, according to the different contributions of different face regions, a differential weight EMN algorithm is proposed to deal with the weight distribution of face sub-regions. Experimental results demonstrate that the proposed algorithm exhibits superior performance compared with the original and other improved HOG algorithms on JAFFE and CK+ datasets.

Keywords: Differential weight; Facial expression recognition; Multi-dimension and multi-scale HOG; Spatial pyramid (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10878-022-00935-1

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