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  • 學位論文

一個自動偵測人臉位置及決定最佳人臉代表之自動化系統

An Automatic System for locating human face and determining the best representative among face photos

指導教授 : 林啟芳

摘要


隨著電腦設備的日漸進步及監控設備的普及化,透過後端電腦的處理讓傳統純監視的監控系統逐漸發展出更多附加的功能,尤其是利用電腦自動化來取代人力的使用更是最重要的發展。 本論文就針對自動化提出了一個自動偵測人臉位置及決定最佳人臉代表之自動化系統。其方法首先是利用預設背景與輸入影像相減求出前景區塊,及利用相鄰的連續影像序列得到移動資訊後,兩者運算即可得到前景移動物體的區塊範圍,之後系統就針對此區塊做膚色偵測,並利用眼睛的特徵驗證該膚色區塊是否為人臉,最後把所有儲存的人臉影像做評估運算找出最佳的人臉影像代表。

並列摘要


In the past few years, the need of detecting human faces plays an important role in many visual applications, and the amount of related technologies are growing rapidly. There are many technologies of human face location, and the method by using the skin color of face to segment the face scope is one of the most commonly used technologies. However, there are many problems about this method, so it is difficult to segment the human face correctly from the background when the background color is close to the skin color. In this paper, we propose an automatic system for locating human face and determining the best representative among face photos. We combine several methods, including moving detection, skin color detection, and feature detection, to locate the positions of human face. When all detections is finished, the system will select the best representative among face photos.

並列關鍵字

Face detection Moving detection

參考文獻


[12]Sanjay Kr. Singh, D. S. Chauhan, Mayank Vatsa, Richa Singh, “A robust skin color based face detection algorithm,” Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp. 227-234, 2003.
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[3]S. Satoh, Y. Nakamura, and T. Kanade, “Name-it: naming and detecting faces in news videos,” IEEE Multimedia, Vol. 6, No. 1, pp. 22-35, 1999.
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被引用紀錄


林建璋(2007)。醫院員工之健康促進活動認知及參與程度相關之探討--從健康促進醫院的觀點〔碩士論文,臺北醫學大學〕。華藝線上圖書館。https://doi.org/10.6831/TMU.2007.00121
陳子玲(2012)。運用臉書提升大學生參與健康促進活動意願之研究-以北部某技術學院為例〔碩士論文,元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-2801201415005931

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