摘要
人臉辨識是現今社會上普遍應用的資訊安全管控方案之一。通常臉部辨識系統包含影像拍攝，臉部區域擷取，臉部特徵向量計算，訓練建置人臉特徵向量資料庫，最後進行人臉辨識。一般運用時需要較高階硬體需求，以便快速進行人臉特徵萃取與分析，因此較難以低階的終端硬體設備達成人臉辨識運用，例如門禁管控等。 本研究是利用Microsoft提供的免費臉部辨識服務，將人臉相片透過網路送到雲端平台，計算取得臉部特徵向量，減少龐大且又複雜的照片處理計算需求，因此可以利用樹莓派作為終端硬體設備，實現臉部辨識系統所需功能。 整個系統硬體部分包含樹莓派3、鏡頭模組 (Raspberry Pi Camera Module)與網路，軟體部分使用Raspbian OS、Python3.0及OpenCV做為開發語言。 實作系統功能包含人臉取像，網路控制使用Microsoft臉部辨識服務，人臉特徵萃取與分析，人臉特徵向量資料庫建置及人臉辨識與門禁管控運用；達成機器學習所需的資料收集、訓練、測試與實際使用。
並列摘要
Face recognition is one of the most widely used information security management solutions in today. Usually face recognition system includes image capture, face area capture, face feature vector calculation, training and construction of face feature vector database, and finally face recognition. In general applications, higher hardware performance requirements are needed to quickly extract and analyze face features. Therefore, it is more difficult for low-end hardware devices to achieve face recognition applications such as access control. This study uses the free face recognition service provided by Microsoft to send face photos to the cloud platform through the Internet, and calculates and obtains face feature vectors, reducing the need for large and complex photo processing loading. Therefore, the Raspberry Pi can be used as the terminal hardware device realizes the functions required by the face recognition system. The entire system hardwire consists of the Raspberry Pi 3, Raspberry Pi Camera Module, and network devices. The software include Raspbian OS, Python 3.0, and OpenCV as the development language. Implementation system function include face capture, network control for using Microsoft facial recognition services, face feature extraction and analysis, face feature vector database construction and face recognition and access control management applications; to achieve machine learning required data collection, training, testing and actual use.