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研究生:黃曉娟
研究生(外文):Shiau-Jiuan Huang
論文名稱:控制環境下的手形辨識
論文名稱(外文):A Study of Hand Pose Recognition in Controlled Environments
指導教授:王聖智王聖智引用關係
指導教授(外文):Sheng-Jyh Wang
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電子工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:94
中文關鍵詞:手形辨識
外文關鍵詞:Hand Pose Recognition
相關次數:
  • 被引用被引用:1
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在這篇論文裡,針對連續動作的正面手部影像序列,我們嘗試建構一套手形辨識系統,以自動化方式分析二維手部影像並進而估測三維手形狀態。其中,我們利用影像處理技術從五指張開手部影像中萃取出手部特徵模型,並利用手部特徵模型追蹤後來影像中每一根手指所相對應的區域,來加以分析每一根手指所對應的特徵資訊。之後,根據空間域上擷取出的二維特徵資訊以及時間域上手形變化的連續性,我們利用貝氏決策定理來估測最佳的三維手形狀態。

In this thesis, we try to construct a hand pose recognition system, which can analyze a sequence of 2D images and reconstruct the corresponding 3D hand poses automatically. In the analyzing stage, we apply image processing techniques to build a hand feature model based on the first image frame, in which the hand pose is always in an “open” status. Based on this hand feature model, we detect finger regions and finger features in the following images. Finally, we use Bayesian decision theory to estimate the status of the 3D hand pose, by combining the 2D features in the spatial domain and the hand motion in the temporal domain.

第一章 4
簡介 4
1-1 系統概觀 7
1-2 大綱 7
第二章 9
先前的研究 9
2.1 相關文獻探討 9
2.1.1 以表象為基礎的途徑(APPEARANCE-BASED APPROACH) 9
2.1.2 以手模型為基礎的途徑(MODEL-BASED APPROACH) 12
2.1.2.1 手模型的建立(Hand Modeling) 12
2.1.2.1.1手的皮膚表面描述(Modeling the shape) 12
2.1.2.1.2手的運動描述 (Modeling the kinematics) 13
2.2 二維主曲率估測(CURVATURE ESTIMATION) 18
2.2.1 曲率(CURVATURE) 18
2.2.2 JONG-WANG 所提出的主曲率估測方法 19
第三章 20
手部影像特徵分析 20
3.1 手部影像切割 (HAND SEGMENTATION) 21
3.1.1皮膚色彩分布的分析 (SKIN COLOR DISTRIBUTION ANALYSIS) 22
3.1.2皮膚色彩分劃法(SKIN COLOR-BASED THRESHOLDING ) 23
3.1.3 手部影像切割實驗結果(SEGMENTATION RESULT) 24
3.2 手部特徵擷取 (HAND FEATURE EXTRACTION) 25
3.2.1 手掌區域擷取 (PALM REGION EXTRACTION) 25
3.2.1.1 結構元素(STRUCTURING ELEMENT)大小分析 26
3.2.2 手的方位偵測 (HAND ORIENTATION) 28
3.2.3 手腕位置 (WRIST POSITION) 31
3.2.4 手指區域擷取 (FINGER REGION EXTRACTION) 35
3.2.5 手部區域的高曲率特徵 (HIGH-CURVATURE FEATURE) 37
3.2.5.1 一維手形形狀與高斯曲率分析 38
3.2.5.3 實作結果 39
3.3 手部特徵追蹤(HAND FEATURE TRACKING) 40
3.3.1 手部特徵模型 (HAND FEATURE MODEL) 40
3.3.1.1手指間距判斷 40
3.3.1.2手部特徵模型建立 41
3.3.2 手指特徵辨識 (FINGER FEATURE RECOGNITION) 43
3.3.3 大拇指特徵辨識 (THUMB FEATURE RECOGNITION) 47
3.3.3.1 TM節點位置的修正 48
3.3.3.2 MCP、IP、TIP等節點位置的偵測 48
第四章 55
手形辨識 55
4.1 手模型的建立 (HAND MODELING) 55
4.1.1手指關節的運動與座標係定義 56
MCP節點座標系- 56
PIP節點座標系與DIP節點座標系 - 57
4.1.2大拇指關節運動與座標系定義 58
TM節點座標系- 58
MCP節點座標系- 59
IP節點的座標系- 61
4.2 手模型參數估測 (MODEL PARAMETER ESTIMATION) 62
4.2.1 手指參數估測 (FINGER PARAMETER ESTIMATION) 63
4.2.1.1 正面長度分布和指尖與MCP點相對位置分布的建立 65
4.2.1.2 關節角度空間篩選與指尖位置範圍統計 69
4.2.1.3 指尖位置的預測與修正 71
4.2.1.4 最佳的手關節角度估測 73
4.2.1.5 實作過程 75
4.2.2 大拇指參數估測 (THUMB PARAMETER ESTIMATION) 88
4.2.2.1 MCP節點與IP節點的 角度估測 88
4.2.2.2 TM節點的 角度估測 88
4.2.2.3 實作結果 90
第五章 93
結論 93
REFERENCE 94

[1] V. Athitsos and S. Sclaroff, “3D hand pose estimation by finding appearance-based matches in a large database of training views”, in IEEE Workshop on Cues in Communication, 2001
[2] Y. Cui, D. Swets, and J. Weng, “Learning-based hand sign recognition using shoslif-m”, in ICCV, 1995 [1] J. Davis, and M. Shah, “Visual gesture recognition,” Vision, Image, and Signal Processing, vol.141, pp.101-106, Apr.1994.
[3] J. Davis and M. Shah, “Visual gesture recognition,” Vision, Image, and Signal Processing, vol.141, pp.101-106, Apr.1994.
[4] W. Freeman, D. Anderson, P. Beardsley, et al, “ Computer vision for interactive computer graphics”, IEEE Computer Graphics and Applications, Vol. 18, Num 3, pages 42-53, May-June 1998
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[6] J.J. Kuch, and T.S. Huang, “Vision-based hand modeling and tracking for virtual teleconferencing and telecollaboration,” in Proc. IEEE Int. Conf. Computer Vision, Cambridge, MA, June 1995, pp.666-671.
[7] J. J. Kuch, and T.S. Huang. “Model-based tracking of self-occluding articulated objects” in Vision based hand modeling and tracking for virtual teleconferencing and telecollaboration, pages 666-671, Cambridge, MA, June 1995
[8] J. Lee, and T. L.Kunii “Model-based analysis of hand posture” IEEE Computer Graphics and Applications , Volume: 15 Issue: 5 , Sept. 1995 Page(s): 77 -86
[9] J. M. Rehg, and T. Kanade. “DigitEyes: Vision-based human hand tracking” Technical report, School of Computer Science, Carnegie Mellon University, December 1993
[10] N. Shimada, K. Kimura, and Y. Shirai, “Real-time 3-d hand posture estimation based on 2-d appearance retrieval using monocular camera”, in Proc. 2nd Int. Workshop on Recognition, Analysis and Tracking of Faces and Gestures in Real Time Systems, pages 23--30, Vancouver, Canada, July 2001
[11] E. Ueda, Y. Matsumoto, M. Imai, and T. Ogasawara, “Hand Pose Estimation using multi-viewpoint silhouette images” Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on , Volume: 4 , 2001
Page(s): 1989 -1996 vol.4
[12] Y. Wu, J. Lin, and T. S. Huang, "Capturing Natural Hand Articulation", in Proc. IEE Int'l Conf. on Computer Vision (ICCV'2001), Vancouver, July, 2001.
[13] Y. Wu, and T.S. Huang, "Capturing Articulated Human Hand Motion: A Divide-and-Conquer Approach ", Proc. of the IEEE Int'l Conf. on Computer Vision, 1999
[14] Y. Wu and T.S. Huang, “View-independent recognition of hand postures”, in CVPR, volume 2, pages 88--94, 2000

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