Human Face Detection and Tracking Using RetinaFace Network for Surveillance Systems

Wibowo, Moh. Edi and Ashari, Ahmad and Subiantoro, Ardacandra and Wahyono, Wahyono (2021) Human Face Detection and Tracking Using RetinaFace Network for Surveillance Systems. In: IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 13-16 October 2021, Toronto, Canada.

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Abstract

Face detection is the main component in the development of CCTV-based Intelligent Surveillance System. Face Detection is used to identify a person when a suspicious event occurs. Therefore, the face detection module must be reliable and fast in analyzing every frame produced by CCTV. RetinaFace is a deep learning-based face detection method that produces very high accuracy. However, RetinaFace cannot be fully implemented directly on the ISS due to limitations in detecting faces in environments with illumination changes. Thus, in this paper, we propose to utilize the detection-based tracking to improve the detection results of RetinaFace as post-processing stages. The tracking system successfully increases the recall score of the detection of faces on recordings with 25 FPS by 4.47. © 2021 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 3
Uncontrolled Keywords: Deep learning; Monitoring; Security systems; Face detection and tracking; Face detection methods; Face detection module; Faces detection; High-accuracy; Human face detection; Intelligent surveillance systems; Retinaface; Surveillance systems; Tracking; Face recognition
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Mathematics and Natural Sciences > Computer Science & Electronics Department
Depositing User: Sri JUNANDI
Date Deposited: 30 Oct 2024 00:29
Last Modified: 30 Oct 2024 00:29
URI: https://ir.lib.ugm.ac.id/id/eprint/8468

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