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研究生: 林曉薇
論文名稱: 基於角度的自拍照品質評估
指導教授: 葉梅珍
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 中文
論文頁數: 28
中文關鍵詞: 自拍照頭部姿態評估三角形特徵品質評估
英文關鍵詞: Selfie, head pose estimation, triangle patterns, quality assessment
論文種類: 學術論文
相關次數: 點閱:158下載:3
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  • 近年來由於智慧型手機的興起,使得自拍成為流行事物之一。然而,對多數人來說要拍攝一張好看的自拍照並不容易。我們提出一個新的方法來幫助使用者拍攝好看的自拍照。本論文中所使用的方法是基於角度估測頭部姿態及三角形特徵作分析。我們的方法主要是從400張正妹自拍照中找出好看的自拍照共通特徵以評估自拍照分數。透過觀察我們發現,多數人自拍時不一定會正臉朝鏡頭,頭部會有傾斜及旋轉。因此,我們對自拍照頭部的x、y、z軸三個角度分別進行估測。除此之外,我們根據頭部姿態對正妹照作分群,從每個分群當中找出頻繁出現的三角形特徵,並利用Labeled Faces in the Wild (LFW)人臉資料庫中12973張一般人臉照同樣頻繁出現的三角形特徵進行過濾。在實驗中,我們使用一組不同角度的3D模擬自拍照來評測效能。比較我們的方法及25位受測者對模擬自拍照的好看程度排序的相關係數,其中有17位受測者的排序與我們方法的排序呈中度相關及高度相關。我們的方法所排列前四名中必有一張存在於25名受測者排序的前四名中。我們的方法有助於使用者進行自拍及挑選自拍照。

    Taking selfies becomes popular in recent years. However, taking a good selfie is not easy for most people. We present a new approach to help user take a good selfie. Specifically, the proposed approach is based on angle analysis in which facial landmarks are used to estimate head pose and identify useful features named triangle patterns. One of the contributions of the thesis is the discovery of common patterns from 400 attractive selfies, based upon which a selfie is rated. We observed that people usually do not show a frontal face to the camera when taking selfies. Therefore, we calculated three angles of head pose, including pitch, yaw and roll. In addition, we used a clustering algorithm based on head pose to group attractive selfies and mined common triangle patterns from each cluster. We further filtered those triangle patterns frequently occurring in a general face dataset. In the experiments, we simulated a set of 3D selfies of different angles. We evaluated the performance of the proposed approach by comparing the ranking list obtained by the automatic approach and those from 25 subjects. 68% of the rankings reach moderately positive correlation by using the proposed method. The results demonstrate that our method can effectively help some users select good selfies.

    第一章 簡介 1 1.1 研究背景與動機 1 1.2 系統架構 3 1.3 論文架構 3 第二章 相關研究探討 4 第三章 自拍照頭部姿態評估 6 3.1 人臉特徵點 7 3.2 頭部姿態計算 7 3.2.1 頭部y軸旋轉角度計算 8 3.2.2 頭部z軸旋轉角度計算 9 3.2.3 頭部x軸旋轉比例計算 11 第四章 三角形特徵選取及評分 12 4.1 分群 12 4.2 三角形特徵 13 4.3 參數設定 15 4.4 加權 16 4.5 特徵合併 16 第五章 實驗結果 19 5.1實驗設置 19 5.2實驗結果與分析 20 第六章 結論 26 參考著作 27

    [1] 臉書正妹牆The Beauty of Facebook
    http://beauty.zones.gamebase.com.tw/wall
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    [3] Matija Males, Aam Hedi, and Mislav Grgic, “Aesthetic Quality Assessment of Headshots”, Proceedings of ELMAR, Zadar, Croatia, pp. 89-92, 2013 .
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    [5] Poliang Shih, “Feature-Vector Based Face Recognition System for Mobile Photos”, Master Thesis, Department of Electronic Engineering, National Chung Cheng University, Taiwan, 2004.
    [6] Jia-ji Huang, “Automatic Face Recognition based on Head Pose Estimation and SIFT Features” Master Thesis, Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan, 2009.
    [7] Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller, “Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments” University of Massachusetts, Amherst, Technical Report 07-49, October, 2007.
    [8] Xuehan Xiong and Fernando De la Torre, “Supervised Descent Method and its Applications to Face Alignment”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2013.
    [9] 人體計測資料庫
    http://www.ilosh.gov.tw/wSite/lp?ctNode=665&mp=11
    [10] R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules in Large Database,” Proceedings of International Conference on Very Large Data Bases, pp. 487-499, 1994.
    [11] http://www.facegen.com/

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