The reprojection process is a crucial step in 3D object tracking, which is used to obtain the object’s 3D points to optimize pose. Although multiple reprojections can significantly improve the accuracy, it is also a time-consuming process, especially when reading the depth buffer from video memory. In this paper, we propose a fast 3D object tracking framework to improve the calculation efficiency, which reduces the reprojection process to one time while keeping the optimization accuracy. We first use geometric contour to estimate a coarse pose fastly, in which process we avoid the reprojection process by utilizing the object’s geometric properties. Then we use the local region to refine the pose precisely while reducing the reprojection process to one time. We further propose a faster version, which can achieve 40 FPS on a mobile phone by sacrificing some accuracy. Experiments show that the proposed method can achieve results comparable to the state-of-the-art methods, while the efficiency has been nearly doubled, and our faster version can track stably on mobile phones.

重新投影过程是3D对象跟踪中的关键步骤，用于获取对象的3D点以优化姿势。尽管多次重投影可以显着提高精度，但这也是一个耗时的过程，尤其是在从视频内存读取深度缓冲区时。在本文中，我们提出了一种快速的3D对象跟踪框架，以提高计算效率，在保持优化精度的同时，将重投影过程减少到一次。我们首先使用几何轮廓来快速估计粗略姿势，在此过程中，我们通过利用对象的几何特性避免了重新投影过程。然后，我们使用局部区域精确地调整姿势，同时将重投影过程减少到一次。我们进一步提出了一个更快的版本，通过牺牲准确性可以在手机上达到40 FPS。实验表明，该方法可以达到与最新方法相当的结果，而效率几乎提高了一倍，而且我们的更快版本可以在手机上稳定跟踪。