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研究生： 程敬智
Ching-chih Cheng
論文名稱： 以整合式子空間分析為基礎之多角度人臉辨識
Multi-view Face Recognition with Unified Subspace Analysis
指導教授： 范國清
Kuo-Chin Fan
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度： 98
語文別： 中文
論文頁數： 64
中文關鍵詞： 整合式子空間 、多角度人臉辨識
外文關鍵詞： Unified Subspace, Multi-view Face Recognition
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    • 人臉辨識的研究迄今已有數十年的發展，其研究成果已能在機場的安檢系統、社區的門禁系統、ATM的認證或諸如許多商業化的NB影像認證等相關的安全辨識應用中發現其蹤影，但在上述的監控應用中，其辨識效果的好壞往往會受到表情、視角、光影、原始影像的解析度等因子所左右，也因為如此，一直以來都有許多相關的研究專門處理相對應的問題。
    然而以現階段的研究來說，大多數的演算法對於具有角度變化的人臉辨識問題仍沒有一個很好的處理方法，因此本論文提出了一個兩階式的辨識方法，首先對輸入影像的視角做第一階段的預測，之後針對視角預測的結果進一步的辨識出其所屬的類別，這樣做的好處不但可以排除視角變化較劇烈的影像集，又可以減少影像比對的次數。
    在實驗的部分，我們將漸進式的呈現出單一視角以及多重視角的實驗數據，實驗的最後我們可以得知，視角預測的前處理步驟可以對整個辨識系統的效能達到一定程度的提升。

    Face recognition technique has been developed for several years. The research results can be found in several applications, such as airport security system, access control system, ATM verification system, and surveillance system. However, the performance of identification result will be heavily affected by the factors of expression, pose, illumination and resolution of image. Hence, many relating algorithms were developed focusing on resolving these problems.
    Until now, most of the existing algorithms can still not fully resolve the pose problem in face recognition. In response to this need, we present a two stage identification method to improve the performance of face recognition system handling pose problem. In our proposed method, we first predict the pose variations for all input images. After that, we further classify the image class in the corresponding pose label set. The advantage of our proposed method can not only eliminate the difference in different pose sets but also reduce image matching time for recognition. Experimental results reveal that the proposed face recognition method with pose classifier can achieve better classification result.

    摘要 ............................................................................................................................. i Abstract .................................................................................................................... ii 目錄 …....................................................................................................................... iv 附圖目錄 .................................................................................................................... v 附表目錄..................................................................................................................... vi 第一章 緒論 .............................................................................................................. 1 1.1 研究動機 .............................................................................................. 1 1.2 人臉辨識系統之基本架構.................................................................... 2 1.3 文獻探討................................................................................................ 3 1.4 系統架構之摘要.................................................................................. 10 1.5 學位論文架構...................................................................................... 11 第二章 相關研究...................................................................................................... 12 2.1 主成分分析(Principal Component Analysis, PCA) ...................... 13 2.2 線性有鑑別度分析(Linear Discriminant Analysis, LDA) .......... 14 2.3 貝氏分類方法(Bayesian classifier) ............................................ 16 2.4 混合式子空間之方法(hybrid subspace method) ........................... 18 第三章 兩階段式之多角度人臉辨識...................................................................... 25 3.1 基於整合式子空間之多角度個體分類方法...................................... 25 3.2 視角辨識方法...................................................................................... 35 3.3 兩階段式之多角度人臉辨識.............................................................. 39 第四章 實驗及討論….............................................................................................. 41 4.1 人臉資料庫之實驗環境介紹.............................................................. 41 4.2 單一視角之實驗結果及其分析.......................................................... 47 4.3 多重視角之實驗結果及其分析.......................................................... 52 第五章 結論與未來工作.......................................................................................... 57 5.1 結論...................................................................................................... 57 5.2 未來工作.............................................................................................. 58 參考文獻.................................................................................................................. 59 附錄A....................................................................................................................... 62 附錄B....................................................................................................................... 64

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