  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.
