簡易檢索 / 詳目顯示

研究生: 林鉦翔
Lin, Jen-Shiang
論文名稱: 於視訊影像之穴道定位
Acupoint Localization from Video Images
指導教授: 詹寶珠
Chung, Pau-Choo
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年: 2009
畢業學年度: 97
語文別: 英文
論文頁數: 37
中文關鍵詞: 質心座標定位穴道
外文關鍵詞: Localization, Acupoint, Barycentric coordinate
相關次數: 點閱:80下載:4
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 準確的穴道定位是提供高效能的按摩療程之基礎,根據中醫理論對於「穴道」的介紹,人體背部的穴道是根據於體型之比例而位於脊椎的兩側。由這個立論所述,標記有正確脊椎棘突點與穴道點之人體背部,則可以被視為提供參考用之模型。因此我們提出背部邊界線對應的方法轉換標準資訊至未知的人體背部,並以定界框為背部區域比例之估算,以相對應之定界框提供的轉換矩陣去實現邊界對應。脊椎棘突點的對應則可由轉換相異背部其邊界線之對應點所產生的三角形質心座標所定位,而對應脊椎點的資訊能在背部分劃出穴道點應該出現的區塊,以標準模型之區塊與對應區塊所求得之轉換矩陣達到準確的穴道定位。我們分別經由自身模型與多張不同姿勢及多組模型與多張不同人體的交叉實驗,驗證轉換後之穴道定位的誤差以及準確度。

    Accurately localizing acupoints is our basic stage in offering high performance to massage process. According to the knowledge of Chinese medicine about “Acupoint”, the acupoints on human back are located relative to human spine, following to body ratio. In this approach, model which consists of correct spine points and acupoints on human back is adopted as reference. Concept of back contour matching is one kind of application of transforming different type of body. Bounding boxes are employed to represent the body ratio and provide registration matrix to match the contours. The barycentric coordinate in triangles localize the spine points in different bodies. Following with the spine points, acupoints can be localized in many regions on human back. Registration for matching regions is adopted again to transform the acupoints precisely. The experimented results of localization are made for both error distance and accuracy between reference model and input images in self-model and cross-model transformation.

    Chapter 1 Introduction 1 Chapter 2 Summary of Acupoints 4 Chapter 3 Method 7 3.1 Overview 7 3.2 Reference Model Building 9 3.3 Image Rectification 10 3.4 Contour Segmentation and Matching 11 3.4.1 Skin Color Detection 12 3.4.2 Edge Detection 13 3.4.3 Bounding Box Generation 14 3.4.3.1 Shape of Rectangle Box 14 3.4.3.2 Shape of Trapezoid Box 16 3.4.4 Detail Contour Matching 17 3.5 Spine and Acupoints Localization 20 Chapter 4 Experiment and test result 24 4.1 Model Data Set 24 4.2 Self-Model Transform 27 4.3 Cross Verification and Correctness Rate 28 4.4 Influence of Model Property 33 Chapter 5 Conclusion 35 Reference 36

    [1] 鍾傑, “訂正 針灸穴位解剖圖解”, 正光書局, 1985
    [2] 唐瓊瑜(翻譯), “穴道療法入門”, 同濟書店, 1993
    [3] 芹澤 勝助, “穴道指壓健康百科”, 瑞昇文化事業有限公司, 2002
    [4] George T. Lewith, Peter J. White, and Jeremie Pariente, “Investigating Acupuncture Using Brain Imaging Techniques:The Current State of Play”, Evid Based Complement Alternat Med, vol. 2(3), pp. 315-319, 2005
    [5] MARK AIRD, B.H.Sc. (Acupuncture), Ph.D. (Cand.), DEIRDRE M. COBBIN, Ph.D., and CAROLE ROGERS, Ph.D., “A Study of the Relative Precision of Acupoint Location Methods”, THE JOURNAL OF ALTERNATIVE AND COMPLEMENTARY MEDICINE, vol. 8, pp. 635-642, 2002
    [6] Chun-Rong Huang, Chu-Song Chen, and Pau-Choo Chung, “Contrast context histogram---An efficient discriminating local descriptor for object recognition and image matching”, Pattern Recognition, vol. 41, pp. 3071-3077, 2008
    [7] Haibin Ling and David W. Jacobs, “Deformation Invariant Image Matching”, Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, vol. 2, pp. 1466-1473, 2005
    [8] David G. Lowe, “Distinctive Image Features from Scale-Invariant Keypoints”, International Journal of Computer Vision, vol. 60, pp. 91-110, 2004
    [9] M.T. Rahman, M.A. Al-Amin, Bin Bakkre, J. Chowdhury, A.R. Bhuiyan, and M.A.-A., “A novel approach of image morphing based on pixel transformation”, Computer and Information Technology, 2008. ICCIT 2008. 10th International Conference on, pp. 1-5, 2007
    [10] J.-S. Pierrard and T. Vetter, “Skin Detail Analysis for Face Recognition”, Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on, pp. 1-8, 2007
    [11] Hosub Yoon, Dohyung Kim, Suyoung Chi, Youngjo Cho, “A robust human head detection method for human tracking”, Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, pp. 4558-4563, 2006
    [12] Richard Hartley, Andrew Zisserman, “Multiple View Geometry in Computer Vision Second Edition”, Cambridge University Press, March 2004
    [13] Zhengyou Zhang, “A Flexible New Technique for Camera Calibration”, Technical Report MSR-TR-98-71, Microsoft Research, Dec. 1998
    [14] Carsten Rother, “A new approach to vanishing point detection in architectural environments”, Image and Vision Computing, vol. 20, pp. 647-655, 2002
    [15] Roman Pflugfelder, Horst Bischof, “People tracking across two distant self-calibrated cameras”, Advanced Video and Signal Based Surveillance, pp. 393-398, Sept. 2007
    [16] P. Kakumanu, S. Makrogiannis, and N. Bourbakis, “A survey of skin-color modeling and detection methods”, Pattern Recognition, vol. 40, pp. 1106-1122, 2007
    [17] J. Kovac, P. Peer, and F. Solina, “Human skin colour clustering for face detection”, EUROCON 2003. Computer as a Tool. The IEEE Region 8, vol. 2, pp. 144-1478, 2003
    [18] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing (2nd Edition)”, Prentice Hall, 2002
    [19] J. Pilet, V. Lepetit, and P. Fua, “Real-time nonrigid surface detection”, Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, vol. 1, pp. 822-828, 2005
    [20] J. Pilet, V. Lepetit, and P. Fua, “Fast Non-Rigid Surface Detection, Registration and Realistic Augmentation”, International Journal of Computer Vision, vol. 76, pp. 109-122, 2008

    下載圖示 校內:2019-08-28公開
    校外:2019-08-28公開
    QR CODE