In this paper we propose a method that estimates the $SE(3)$ continuous trajectories (orientation and translation) of the dynamic rigid objects present in a scene, from multiple RGB-D views. Specifically, we fit the object trajectories to cumulative B-Splines curves, which allow us to interpolate, at any intermediate time stamp, not only their poses but also their linear and angular velocities and accelerations. Additionally, we derive in this work the analytical $SE(3)$ Jacobians needed by the optimization, being applicable to any other approach that uses this type of curves. To the best of our knowledge this is the first work that proposes 6-DoF continuous-time object tracking, which we endorse with significant computational cost reduction thanks to our analytical derivations. We evaluate our proposal in synthetic data and in a public benchmark, showing competitive results in localization and significant improvements in velocity estimation in comparison to discrete-time approaches.
翻译:在本文中,我们提出一种方法,从多个 RGB-D 视图中估算一个场景中动态僵硬物体的连续轨迹(方向和翻译),从多个 RGB-D 视图中估算3美元。具体地说,我们将对象轨迹与累积的B-Spline曲线相匹配,从而使我们能够在任何中间时间进行内插,不仅其外形,而且其线形和角形速度和加速度。此外,我们从这项工作中得出优化所需的分析费用(3)美元,适用于使用这种曲线的任何其他方法。我们最了解的是,这是提出6-DoF 连续时间目标跟踪的第一个工作,由于我们的分析推算,我们赞同这种连续时间跟踪,并大大降低了计算成本。我们评价了我们在合成数据和公共基准方面的建议,在与离散时间方法相比,显示地方化的竞争性结果和速度估计方面的重大改进。