政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/112676
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51609973      Online Users : 807
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/112676


    Title: 基於近紅外線影像之年齡層估算機制
    A mechanism for age classification using near-infrared images
    Authors: 林言翰
    Lin, Yan-Han
    Contributors: 郭耀煌
    廖文宏
    Kuo, Yau-Hwang
    Liao, Wen-Hung
    林言翰
    Lin, Yan-Han
    Keywords: 年齡估計
    近紅外線影像
    局部二值模式
    RealSense攝影機
    Age estimation
    Near infrared
    Local Binary Patterns
    RealSense camera
    Date: 2017
    Issue Date: 2017-09-13 14:47:33 (UTC+8)
    Abstract: 近紅外線影像由於其物理特性與成像方式，其紋理細節都有發散模糊不清的現象，對於以紋理為主要特徵的年齡辨識問題而言更具挑戰。本論文主要目的是以近紅外線人臉影像為基礎，找出對近紅外線年齡特徵有最佳描述力的特徵描述子，辨識近紅外線影像中被拍攝者的年齡區間，建構整個年齡層估算機制。
    相關研究一部分關注可見光年齡辨識，另一部分則聚焦在近紅外線人臉辨識，目前還沒有近紅外線年齡辨識的相關文獻能參考，如何從接近的研究領域找尋是適當的演算法是本研究遇到的第一個挑戰。在資料庫的部分，FGNET和MORPH常被用於可見光的年齡辨識議題； PolyU和LDHF則用於近紅外線人臉辨識相關研究，在目前沒有近紅外線年齡資料庫的情況，本研究自建RSNIR（Intel RealSense Near-Infrared Age Database），因此如何標準化拍攝環境流程、蒐集穩定的近紅外線影像是本研究面臨的第二個挑戰。
    區域性特徵擷取方法的關鍵在於特徵描述子的描述力。本研究以LBP（Local Binary Patterns）為基礎，探討LBP在內的24個特徵描述子，最後實驗測試各個描述子在RSNIR的辨識率，結果發現基本型Fuzzy LBP和擴充型RILBP對近紅外線年齡特徵有最佳描述力。在空間譜子區塊（patch）設計部分，以3x3切割子區塊數的辨識效果最好，反應出其與影像校正時的人臉影像空間定義方式有關。
    Reference: [1] Burnay, S. G., T. L. Williams, and C. H. Jones, eds. Applications of thermal imaging. CRC Press, 1988.
    [2] 薛玉利. 基于 Gabor 变换的特征提取及其应用. MS thesis. 山东大学, 2007.
    [3] Ojala, Timo, Matti Pietikainen, and Topi Maenpaa. "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.7 （2002）: 971-987.
    [4] Tan, Xiaoyang, and Bill Triggs. "Enhanced local texture feature sets for face recognition under difficult lighting conditions." Analysis and Modeling of Faces and Gestures. Springer Berlin Heidelberg, 2007. 168-182.
    [5] Liao, Wen-Hung. "Region description using extended local ternary patterns. "Pattern Recognition （ICPR）, 2010 20th International Conference on. IEEE, 2010.
    [6] Liao, Wen-Hung. "Commensurate dimensionality reduction for extended local ternary patterns." Pattern Recognition （ICPR）, 2012 21st International Conference on. IEEE, 2012.
    [7] Altman, Naomi S. "An introduction to kernel and nearest-neighbor nonparametric regression." The American Statistician 46.3 （1992）: 175-185.
    [8] Guo, Guodong, Stan Z. Li, and Kapluk Chan. "Face recognition by support vector machines." Automatic Face and Gesture Recognition, 2000. Proceedings. Fourth IEEE International Conference on. IEEE, 2000.
    [9] Burges, Christopher JC. "A tutorial on support vector machines for pattern recognition." Data mining and knowledge discovery 2.2 （1998）: 121-167.
    [10] The FG-NET Aging Database, http://www.fgnet.rsunit.com/, http://www-prima.inrialpes.fr/FGnet/, 2010.
    [11] Ricanek Jr, Karl, and Tamirat Tesafaye. "Morph: A longitudinal image database of normal adult age-progression." Automatic Face and Gesture Recognition, 2006. FGR 2006. 7th International Conference on. IEEE, 2006.
    [12] MORPH Face Database, http://faceaginggroup.com/, 2010.
    [13] PolyU NIR Face Database, http://www4.comp.polyu.edu.hk/~biometrics/polyudb_face.htm, 2010.
    [14] Hsu, Rein-Lien, Mohamed Abdel-Mottaleb, and Anil K. Jain. "Face detection in color images." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.5 （2002）: 696-706.
    [15] Yang, Ming-Hsuan, and Narendra Ahuja. "Detecting human faces in color images." Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on. Vol. 1. IEEE, 1998.
    [16] Viola, Paul, and Michael Jones. "Rapid object detection using a boosted cascade of simple features." Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. Vol. 1. IEEE, 2001.
    [17] Lienhart, Rainer, and Jochen Maydt. "An extended set of haar-like features for rapid object detection." Image Processing. 2002. Proceedings. 2002 International Conference on. Vol. 1. IEEE, 2002.
    [18] Liao, Shengcai, et al. "Learning multi-scale block local binary patterns for face recognition." Advances in Biometrics. Springer Berlin Heidelberg, 2007. 828-837.
    [19] Fu, Yun, Guodong Guo, and Thomas S. Huang. "Age synthesis and estimation via faces: A survey." Pattern Analysis and Machine Intelligence, IEEE Transactions on 32.11 （2010）: 1955-1976.
    [20] Jabid, Taskeed, Md Hasanul Kabir, and Oksam Chae. "Local directional pattern （LDP） for face recognition." 2010 Digest of Technical Papers International Conference on Consumer Electronics （ICCE）. 2010.
    [21] Ahonen, Timo, Abdenour Hadid, and Matti Pietikäinen. "Face recognition with local binary patterns." Computer vision-eccv 2004. Springer Berlin Heidelberg, 2004. 469-481.
    [22] R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed., Reading, MA: Addison-Wesley, 1992.
    [23] Pizer, Stephen M., et al. "Adaptive histogram equalization and its variations." Computer vision, graphics, and image processing 39.3 （1987）: 355-368.
    [24] Zuiderveld, Karel. "Contrast limited adaptive histogram equalization." Graphics gems IV. Academic Press Professional, Inc., 1994.
    [25] Turk, M., and Pentland, A. Eigenfaces for recognition. Journal of Cognitive Neuroscience 3 （1991）, 71–86.
    [26] Belhumeur, P. N., Hespanha, J., and Kriegman, D. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 7 （1997）, 711–720.
    [27] Hafiane, Adel, Guna Seetharaman, and Bertrand Zavidovique. "Median binary pattern for textures classification." International Conference Image Analysis and Recognition. Springer, Berlin, Heidelberg, 2007.
    [28] Jin, Hongliang, et al. "Face detection using improved LBP under Bayesian framework." Image and Graphics （ICIG`04）, Third International Conference on. IEEE, 2004.
    [29] Heikkilä, Marko, Matti Pietikäinen, and Cordelia Schmid. "Description of interest regions with center-symmetric local binary patterns." ICVGIP. Vol. 6. 2006.
    [30] Ahonen, Timo, and Matti Pietikäinen. "Soft histograms for local binary patterns." Proceedings of the Finnish signal processing symposium, FINSIG. Vol. 5. No. 9. 2007.
    [31] Ahonen, Timo, Abdenour Hadid, and Matti Pietikainen. "Face description with local binary patterns: Application to face recognition." IEEE transactions on pattern analysis and machine intelligence 28.12 （2006）: 2037-2041.
    [32] Ojala, Timo, Matti Pietikainen, and David Harwood. "Performance evaluation of texture measures with classification based on Kullback discrimination of distributions." Pattern Recognition, 1994. Vol. 1-Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on. Vol. 1. IEEE, 1994.
    Description: 碩士
    國立政治大學
    資訊科學學系
    102753013
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102753013
    Data Type: thesis
    Appears in Collections:[Department of Computer Science ] Theses

    Files in This Item:

    File SizeFormat
    301301.pdf7995KbAdobe PDF2124View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback