| Summary: | 碩士 === 國立中正大學 === 資訊工程學系碩士在職專班 === 105 === Abstract
Most of conventional techniques applied by facial recognition include data collection, classification, preprocessing, standardization, identification, searching, etc. Now, ADSA (Advanced Driver Assistance Systems) is a successful and important application based on the technique of facial recognition to detect the dynamic and instant driving situations concerning about the driver, passengers inside or near the car and then successively provides a safe guide for further driving. In this application, the streaming video is required to be processed by the real-time response. Until now, we can find that a couple of conventional applications based on the techniques of facial recognition are required to have the processing ability of real-time responsibility.
In this research, we try to propose some real-time solutions not only for finding user’s face, but also user’s characteristics including expression, mood, etc. We build a streaming server to collect the instant data scanning from a Raspberry Pi device. Then, we design some processing algorithms based on PCA and LDA on the server site to realize the proposed tasks of facial recognition. Our results can almost reach the real-time requirement. For further research, we will redesign the structure of projection space to solve the over fitting problem due to the successively coming big data of facial images.
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