A face cropping strategy for facial expression recognition

Fangyu Feng; Xiaoshu Luo; Guangyu Wang

doi:10.1117/12.2661078

22 November 2022 A face cropping strategy for facial expression recognition

Fangyu Feng, Xiaoshu Luo, Guangyu Wang

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 1247523 (2022) https://doi.org/10.1117/12.2661078
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

In the process of facial expression recognition by convolutional neural network, aiming at the problem that the complex background interferes with the extraction of expression features, a simple face cropping strategy is proposed. First, the critical facial expression regions are calculated by face alignment and landmarks detection, thus the background influence outside the facial expression region is reduced, and then the convolutional neural network is used to further extract expression features and enable expression classification. The experimental results show that the facial expression recognition effect is significantly improved by the proposed method, and the recognition accuracy on the facial expression datasets JAFFE and CK+ reaches 90.48% and 96.67%, respectively.

Citation Download Citation

Fangyu Feng, Xiaoshu Luo, and Guangyu Wang "A face cropping strategy for facial expression recognition", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 1247523 (22 November 2022); https://doi.org/10.1117/12.2661078

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KEYWORDS

Facial recognition systems

Convolutional neural networks

Feature extraction

Image processing

Sensors

Image classification

Eye

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