...
首页> 外文期刊>Image and Vision Computing >Kinematic sets for real-time robust articulated object tracking
【24h】

Kinematic sets for real-time robust articulated object tracking

机译:运动学集,用于实时鲁棒的关节运动目标跟踪

获取原文
获取原文并翻译 | 示例

摘要

In this article, a new approach is given for real-time visual tracking of a class of articulated non-rigid objects in 3D. The main contribution of this paper consists in symmetrically modeling the motion and velocity of an articulated object via a novel kinematic set approach. This is likened to a Lagrange-d'Alembert formulation in classical physics. The advantages of this new model over pre-existing methods include improved precision, robustness and efficiency, leading to real-time performance. Furthermore, a general class of mechanical joints can be considered and the method can track objects where previous approaches have failed due to a lack of visual information. In summary, a joint configuration is modeled by using Pfaffian velocity constraints. The configuration and location of a joint is then used to build a general Jacobian Matrix, which relates individual rigid body velocities (twists) to an underlying minimal subspace. A closed loop control law is then derived in order to minimize a set of distance errors in the image and estimate the system parameters. The tracking is locally based upon efficient distance criterion. Experimental results show prismatic, rotational and helical type links and eight general parameters. A statistical M-estimation technique is applied to improve robustness. A monocular camera system was used as a real-time sensor to verify the theory.
机译:在本文中,提供了一种新方法,用于实时视觉跟踪3D中一类铰接的非刚性对象。本文的主要贡献在于通过一种新颖的运动学设置方法对关节物体的运动和速度进行对称建模。这可以比作经典物理学中的Lagrange-d'Alembert公式。与现有方法相比,该新模型的优势包括提高了精度,鲁棒性和效率,从而带来了实时性能。此外,可以考虑机械关节的一般类别,并且该方法可以跟踪由于缺少视觉信息而导致先前方法失败的对象。总而言之,使用Pfaffian速度约束对关节构型进行建模。然后,使用关节的配置和位置来构建通用的Jacobian矩阵,该矩阵将各个刚体的速度(扭曲)与下面的最小子空间相关联。然后导出闭环控制定律,以最小化图像中的一组距离误差并估计系统参数。跟踪是基于有效距离标准在本地进行的。实验结果显示了棱柱形,旋转形和螺旋形连接以及八个通用参数。应用统计M估计技术来提高鲁棒性。单眼相机系统被用作实时传感器以验证该理论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号