A one-shot face detection and recognition using deep learning method for access control system

Tsung Han Tsai, Chi En Tsai, Po Ting Chi

研究成果: 雜誌貢獻期刊論文同行評審

摘要

In this paper, we propose a face detection and recognition system using deep learning method. It can be used as an access control system that performs face detection and recognition in real-time processing. Our goal is to achieve a one-shot recognition instead of traditional two-step methods. We use SSD as the main model for face detection and VGG-Face as the main model for face recognition. We perform the deep learning method through the collection of datasets. Moreover, we use some techniques, such as data augmentation, preprocessing of the image, and post-processing of the image to train the robust face detection and recognition subsystems. We use continuous frames as input to avoid false-positive cases and make the system output without wrong results. A real demonstration system is constructed to determine the identification of the laboratory members. We use 1280 × 960 resolution video for experimental testing and achieve about 30 fps speed under GPU acceleration.

原文???core.languages.en_GB???
頁(從 - 到)1571-1579
頁數9
期刊Signal, Image and Video Processing
17
發行號4
DOIs
出版狀態已出版 - 6月 2023

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