We propose a dense continuous-time tracking and mapping
method for RGB-D cameras. We parametrize the
camera trajectory using continuous B-splines and optimize
the trajectory through dense, direct image alignment. Our
method also directly models rolling shutter in both RGB and
depth images within the optimization, which improves tracking
and reconstruction quality for low-cost CMOS sensors.
Using a continuous trajectory representation has a number
of advantages over a discrete-time representation (e.g.
camera poses at the frame interval). With splines, less variables
need to be optimized than with a discrete representation,
since the trajectory can be represented with fewer
control points than frames. Splines also naturally include
smoothness constraints on derivatives of the trajectory estimate.
Finally, the continuous trajectory representation allows
to compensate for rolling shutter effects, since a pose
estimate is available at any exposure time of an image. Our
approach demonstrates superior quality in tracking and reconstruction
compared to approaches with discrete-time or
global shutter assumptions.