Texture feature extraction and optimization of facial expression based on weakly supervised clustering

Texture feature extraction and optimization of facial expression based on weakly supervised clustering

In order to improve the recognition rate of weak annotation data in facial expression recognition task, this paper proposes a multi-scale and multi-region vector triangle texture feature extraction scheme based on weakly supervised clustering algorithm. According to the information gain rate of extr...

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Bibliographic Details
Main Authors: Tang Jiaming, Mao Jiafa, Sheng Weiguo, Hu Yahong, Gao Hua
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Systems Science & Control Engineering
Subjects:
facial expression recognition
weakly supervised clustering
texture feature
feature optimization
Online Access:http://dx.doi.org/10.1080/21642583.2021.1943725

Internet

http://dx.doi.org/10.1080/21642583.2021.1943725

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