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    郭康德, 张明敏, 孙 超, 李 扬, 汤 兴. 基于视觉技术的三维指尖跟踪算法[J]. 计算机研究与发展, 2010, 47(6): 1013-1019.
    引用本文: 郭康德, 张明敏, 孙 超, 李 扬, 汤 兴. 基于视觉技术的三维指尖跟踪算法[J]. 计算机研究与发展, 2010, 47(6): 1013-1019.
    Guo Kangde, Zhang Mingmin, Sun Chao, Li Yang, Tang Xing. 3D Fingertip Tracking Algorithm Based on Computer Vision[J]. Journal of Computer Research and Development, 2010, 47(6): 1013-1019.
    Citation: Guo Kangde, Zhang Mingmin, Sun Chao, Li Yang, Tang Xing. 3D Fingertip Tracking Algorithm Based on Computer Vision[J]. Journal of Computer Research and Development, 2010, 47(6): 1013-1019.

    基于视觉技术的三维指尖跟踪算法

    3D Fingertip Tracking Algorithm Based on Computer Vision

    • 摘要: 基于手势的实时人机交互(HCI)在虚拟现实领域有着重要的理论和应用价值.通过双目摄像头,使用立体视觉技术可以实现指尖在三维空间的跟踪定位,进而实现指尖和虚拟空间三维物体的实时交互.这种技术可以实现三维鼠标以及用于虚实交互的三维游戏中.提出一种阈值结合混合多高斯的BGS算法,用它来得到手的区域,然后通过手轮廓K向量和手中心到指尖的距离判定指尖位置,再利用标记对摄像机进行标定,根据标定参数和两个图像中得到的指尖位置,重建指尖点三维坐标,最后在三维空间实施Kalman滤波来平滑指尖点轨迹并预测前景分割的范围.实验结果表明算法是有效的.

       

      Abstract: Realtime human-computer interaction(HCI) based on hand gestures plays an important role in both theory and application of virtual reality. Since the 3D position of fingertip can be tracked and located through stereovision technology with two cameras, the real-time interaction between fingertip and 3D objects in virtual world can be achieved. The proposed method in this paper can be widely used to implement 3D interaction for augmented reality based video games. In this paper, an improved BGS algorithm, which combines threshold decision with GMM, is presented to identify the hand region. The method can get hand region in different lighting conditions, and avoid the interference of cast shadow of hand. The fingertip can be determined with contour Kvector and distance between the hand region center and the candidate fingertip position. Compared with the general fingertip algorithms, the algorithm presented can get fingertips in unfriendly hand foreground segmentation. After calibrating two cameras, the authors get origin position in world coordinate relative to marker center, then 3D position of fingertip can be reconstructed by camera parameters and the fingertip positions in two images taken by the two cameras. Finally, Kalman filter is employed in 3D space to smooth the fingertip trajectory and predict the range of fingertips. Experimental result shows the efficiency of the algorithm.

       

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