研究生: |
卓佑霖 You-Lin Zhuo |
---|---|
論文名稱: |
變化光源下臉部辨識之分析與比較 A Comparative Study on Face Recognition Across Illumination |
指導教授: |
徐繼聖
Gee-Sern Hsu |
口試委員: |
鍾國亮
Kuo-Liang Chung 鐘聖倫 Sern-Lun Chung 洪一平 Yi-Ping Hung 郭景明 Jing-Ming Guo |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 機械工程系 Department of Mechanical Engineering |
論文出版年: | 2011 |
畢業學年度: | 99 |
語文別: | 中文 |
論文頁數: | 53 |
中文關鍵詞: | 對數轉換 、迦瑪校正 、離散餘弦轉換 、高斯差值濾波 、局部外貌法 |
外文關鍵詞: | Logarithm Transform, Gamma Correction, Discrete Cosine Transform, Difference of Gaussian Filtering, Local Appearance-based Algorithm |
相關次數: | 點閱:331 下載:9 |
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人臉辨識相關研究的重點之一在於如何改善並提升非均勻光源環境下的辨識率。最主要的問題為光源在人臉上可產生劇烈的變化,增加了系統辨別人臉特徵的難度,大幅降低了辨識率。近年來的相關研究著重於光源校正、特徵抽取、與分類器設計,但卻缺乏深入的效能評比。本論文挑出幾項有效的光源校正法與數種局部特徵的抽取,配合支持向量機(Support Vector Machines)分類器進行辨識效能的評估與比較,結論出何種光源校正法與局部特徵的搭配有助於變化光源下的臉部辨識。本論文的另一重點為將前述結論出的方法應用於即時系統之製作,分析相關的問題並提出有效的解決方案。本研究採用Face Recognition Grand Challenge(FRGC)資料庫做為實驗的樣本,此資料庫中每一位對象的影像均包含了不同時間、光源環境及表情變化等因素,提升了本研究的挑戰性。實驗應用前述結論的方法達到85.19%之辨識率,而本方法應用於即時系統之製作也極具競爭力。
Face recognition across illumination is one of the most challenging problems in image-based face analysis. Most research focus on the methods for illumination normalization, illumination-invariant feature extraction, or classifier design, but few compare the performance of different approaches. This research evaluates and compares the performance of a few competitive approaches for illumination normalization and several methods for local feature extraction, aiming at determining an effective approach for face recognition across illumination. Because the other issue of the central concern of this research is the appropriateness of the determined approach in making a real-time system, the methods with high computational cost are excluded, although some may result in high recognition rates. The approach recommended by this comparison study can attain 85.19% in recognition rate on FRGC 2.0 database. With its relatively low computational cost, the approach is experimentally proven appropriate for making a real-time system.
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