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dc.contributorChia-Feng Juangen_US
dc.contributor.authorJiang, Hong-Jhangen_US
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[31] Razali M.T. and Asznan B.J., “Detection and classification of moving object for smart vision sensor,” Proc. Information and communication Technologies, vol. 1, pp. 733-737, 2006. [32] T. Horprasert, D. Harwood, and L.S. Davis, “A statistical approach for real-time robust background subtraction and shadow detection,” Proc. IEEE Int. Conf. Computer Vision, Frame-Rate Workshop, pp. 1-19, Freece, Sept. 1999en_US
dc.description.abstract本論文提出一種利用在二維所擷取的人體輪廓資訊以即時估測三維人體重要點的方法。三維的人體重要點包含頭,身體的中心點,雙手及雙腳的末端點,左右肩膀以及手肘和膝蓋。本論文利用一台立體攝影機同時擷取左右兩組連續的影像。首先,利用一種角度補償的色彩三原色分割演算法(AC-RGB segmentation)來從背景中分離出移動的物體,並且降低陰影的影響。然後在兩張各別影像上,利用人體輪廓的凸點、人體幾何的特性、膚色、與時序資訊,來求取頭、雙手及雙腳的末端點的二維位置。手肘和膝蓋點的位置主要利用二維減影求取的骨幹來獲得。最後,重要點的深度資訊是利用同一個點在左右影像得到的二維位置來求取。對於那些左右影像所得到二維位置無法匹配的重要點,本論文利用Kalman Filter 演算法來進行預估與修正。最後,將得到的三維特徵點的座標資訊與所預估的人體方向傳入Virtools這套軟體,建立出虛擬的三維人物模型。實驗結果顯示,相較於其他不同色彩模式的影像分割方法,AC-RGB人體分割的方法,有較佳的分割效果。再者,本論文亦建構出一個即時虛擬三維人體模型系統,來驗證所提出方法得可行性。為了顯示本系統的潛力,亦將其應在一些三維互動式娛樂性遊戲上。zh_TW
dc.description.abstractThis thesis proposes a real-time three-dimensional (3D) human body significant point estimation method by using two-dimensional (2D) extracted body contours. The located 3D body significant points include the head, center of the body, tips of the feet and the hands, the shoulders, the elbows, and the knees. This thesis uses one stereo vision camera to capture both the left and right sets of image sequences at the same time. An Angle-Compensated RGB (AC-RGB) segmentation method is used to segment a moving object from the background in RGB color space and reduce the influence of shadow. In each of the left and right images, 2D locations of the head and tips of the feet and the hands are obtained based on 2D contour convex points, body geometrical characteristics, skin color, and temporal information. Locations of the elbows and the knees are obtained by using the skeleton pixels of a 2D body silhouette. The depth of each significant point is obtained by using the 2D locations of the same point found in the left and right images. The Kalman filter algorithm is used to correct locations of the 3D significant body points and predict the points with mismatching locations from the left and right images. The 3D locations of the significant points and the estimated orientation of the human body are sent to the Virtools software to reconstruct a virtual 3D human model. Experimental results show that the AC-RGB human body segmentation outperforms several segmentation methods used for comparison. This thesis sets up a real-time virtual 3D human model system to verify the effectiveness of the proposed approach. To show the potential of the system, the system is also applied to some 3D interactive entertainment games.en_US
dc.description.tableofcontents摘要 i Abstract ii Content iii Figure Content v Table Content ix Chapter 1 Introduction 1 1.1 Survey 1 1.2 Organization of the Thesis 4 Chapter 2 Angle-Compensated RGB-based Human Body Segmentation 5 2.1 Overview 5 2.2 RGB-based Background Registration And Update 7 2.3 Angle-Compensated RGB Model for Shadow Removal 11 2.4 Post Processing 13 Chapter3 Two-Dimensional Posture Estimation 15 3.1 Overview 15 3.2 Localization of Convex Points 16 3.3 Features for Posture Estimation 17 3.4 Posture Estimation Rules 19 3.5 Locating the Shoulders, Elbows and Knees 22 Chapter 4 Three-Dimensional Significant Points Reconstruction 27 4.1 Overview 27 4.2 Stereo Vision Algorithm 28 4.3 Estimation of 3D Significant Point Locations 30 4.4 Kalman Filter for 3D Significant Points 31 Chapter 5 Virtual 3D Model Construction with Interactive Entertainment Applications Using Virtools 33 5.1 Overview 33 5.2 Orientation Estimation 35 5.3 The First Interactive Game (The Monkey Destroyer) 39 5.4 The Second Interactive Game (The Coach Following) 40 Chapter 6 Experiments 41 6.1 2D Human Body Segmentation Results 42 6.2 2D Significant Points Estimation Results 50 6.3 3D Estimation Results and Constructed 3D Model Using Virtools 66 6.4 Real-Time 3D Experiments 79 Chapter 7 Conclusions 82 References 83zh_TW
dc.subjectcomputer visionen_US
dc.subjectstereo visionen_US
dc.subjectposture estimationen_US
dc.subjectobject segmentationen_US
dc.titleStereo Camera-based Real-Time 3D Virtual Human Construction with Interactive Entertainment Applicationsen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextno fulltext-
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