Face Occlusion Detection Based on SSD Algorithm

Ziwei, Xue; Zhang, Liang; Pu, Jingyu; Zhang, Jinqian; Chen, Hongling; Zhang, Yiwen; Huang, Xi; Xu, Siyuan; Yu, Haoyang

doi:10.1109/iceiec49280.2020.9152335

Cited by 5 publications

(1 citation statement)

References 12 publications

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“…SSD merupakan salah satu metode deteksi objek yang dikembangkan untuk menutupi kelemahan haar cascade. Metode ini sudah diimplementasikan pada deteksi wajah dengan halangan kacamata hitam, syal, alat pernafasan, topi, topeng, kalung, masker [11], SSD mampu menunjukkan kinerja dengan baik.…”

Section: Pendahuluanunclassified

Perbandingan Metode Deteksi Wajah Menggunakan OpenCV Haar Cascade, OpenCV Single Shot Multibox Detector (SSD) dan DLib CNN

Farokhah¹

2021

RESTI

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Comparison of methods in face detection is needed to provide recommendation of best method. This study compared three methods in face detection, namely OpenCV haar cascade, OpenCV Single Shot Multibox Detector (SSD) and Dlib CNN. Face detection is focused on five challenging conditions, namely face detection in head position obstacles, wearing face masks, lighting, background images that have a lot of noise, differences in expression. Data testing is taken randomly on google with reference to one image consisting of more than one detected face with wild condition. The results of the comparative analysis in wild condition show that the OpenCV haar cascade has more weaknesses with a performance percentage of 20% compared OpenCV SSD and Dlib CNN method. Performance results of SSD and Dlib CNN have the same performance in the five conditions tested, which is about 80%.

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Section: Pendahuluanunclassified