Title: Face detection algorithm under low-light based on feature recovery

Authors: Manli Wang; Bingbing Chen; Changsen Zhang

Addresses: School of Physics and Electronic Information, Henan Polytechnic University, Jiaozuo 454000, China ' School of Physics and Electronic Information, Henan Polytechnic University, Jiaozuo 454000, China ' School of Physics and Electronic Information, Henan Polytechnic University, Jiaozuo 454000, China

Abstract: Face detection detects and locates faces in images for face recognition, face tracking, and analysis applications. The performance of many advanced face recognition models deteriorates significantly when applied to low-light environments, hence face detection from low-light images is challenging. To solve the problem, this paper proposes a face detection method based on feature recovery, which includes two modules: feature recovery and feature extraction. The feature recovery module can obtain the face feature recovery image, which is fused with the original low-light face image to obtain the face feature image. On this basis, the feature extraction is trained for face detection. Finally, a face detection method suitable for low-light is obtained. It solves the difficulty of face detection under low-light. The experiment results carried out the overall detection precision increased by 18% on the DARK FACE test set, which verified the effectiveness of the proposed method.

Keywords: low-light; face detection; feature recovery; feature extraction.

DOI: 10.1504/IJCCPS.2023.133730

International Journal of Cybernetics and Cyber-Physical Systems, 2023 Vol.1 No.3, pp.246 - 260

Received: 08 Aug 2022
Accepted: 10 Sep 2022
Published online: 02 Oct 2023 *

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