Karya
Judul/Title Human Face Detection and Tracking Using RetinaFace Network for Surveillance Systems
Penulis/Author Moh. Edi Wibowo, S.Kom.,M.Kom., Ph.D. (1); Prof. Dr. Techn. Ahmad Ashari, M.I.Kom. (2); ARDACANDRA S (3); Wahyono, Ph.D. (4)
Tanggal/Date 13 2021
Kata Kunci/Keyword
Abstrak/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%.
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
1PEER REVIEW_wahyono 12_.pdf[PAK] Peer Review
2human face_merged.pdf[PAK] Full Dokumen
3Human Face Detection and Tracking Using RetinaFace.pdf[PAK] Full Dokumen