计算机应用 ›› 2014, Vol. 34 ›› Issue (5): 1442-1448.DOI: 10.11772/j.issn.1001-9081.2014.05.1442

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于深度图像的运动人手检测与指尖点跟踪算法

刘伟华1,樊养余1,雷涛2   

  1. 1. 西北工业大学 电子信息学院,西安 710072
    2. 兰州交通大学 电子与信息工程学院,兰州 730070
  • 收稿日期:2013-11-05 修回日期:2013-12-18 出版日期:2014-05-01 发布日期:2014-05-30
  • 通讯作者: 刘伟华
  • 作者简介:刘伟华(1986-),男,陕西西安人,博士研究生,主要研究方向:计算机视觉、机器学习、虚拟现实;
    樊养余(1960-),男,陕西蓝田人,教授,博士,主要研究方向:图像处理、模式识别、虚拟现实;
    雷涛(1981-),男,陕西大荔人,副教授,博士,主要研究方向:图像处理、模式识别、计算机视觉
  • 基金资助:

    国家自然科学基金资助项目;中国博士后科学基金资助项目

Human fingertip detection and tracking algorithm based on depth image

LIU Weihua1,FAN Yangyu1,LEI Tao2   

  1. 1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an Shaanxi 710072, China;
    2. School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou Gansu 730070, China
  • Received:2013-11-05 Revised:2013-12-18 Online:2014-05-01 Published:2014-05-30
  • Contact: LIU Weihua
  • Supported by:

    National Natural Science Foundation

摘要:

针对由传统摄像头获得的二维图像难以准确检测复杂环境下运动人手目标的问题,提出了一种利用Kinect摄像头对复杂背景下近景人手指尖空间点的检测和跟踪算法。首先利用基于视觉的多信息融合方法对人手区域进行粗检测,并利用深度信息对得到的模糊人手区域进行精确定位及分割,从而有效抑制了复杂背景对人手区域的干扰;根据分割得到的人手区域,利用人手边界的曲率关系实现了指尖空间点的快速检测;最后利用卡尔曼滤波跟踪检测到的运动指尖点。实验结果表明,与已有指尖点检测方法相比,该算法能够准确地跟踪多种姿态下手指指尖的空间位置,具有较低的误差率。

Abstract:

To solve the problem of detecting human hand in complex background based on traditional camera, a fast, automatic method was proposed which can accurately detect and track foreground human fingertips by using Kinect camera. This method firstly used a combined vision-based information to roughly extract the hand region, then, by taking advantage of depth information, a bare hand could be successfully segmented without connecting to background. Subsequently, the fingertips of that bare hand could be extracted by using minimum circle and curvature relationship on the hand boundary. Finally, to improve the detecting accuracy, the fingertips were optimized by using Kalman filter. The experimental results show that compared with existing method the algorithm can successfully track the 3D locations of fingertips under multiple hand poses and with much lower error rate.

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