Continuous-Time Trajectory Estimation From Noisy Camera Poses Using Cubic Bézier Curves

Recovering the trajectory of a moving camera from image sequences usually generates a set of discrete camera poses. Applications such as view synthesis, sensor data fusion and interactive simulations, however, often require a continuous trajectory. In this work an algorithm for estimating the control points of a cubic Bezler curve is presented and evaluated on the impact of noisy measurement data. With the estimation results a continuous-time representation of the camera's trajectory is recovered and a pose interpolation between the noisy discrete camera poses is realizable. Different levels of noise on translation, rotation and velocity are analysed, whereby the use of straight line trajectories leads to special configurations. The contributions of this paper are as follows: (1) the absolute trajectory error compared on various noisy parameters in characteristic maps (2) the continuous-time trajectory generation combined with special configurations using straight line trajectories and (3) the source code of implementation and measurement examples are released, in order to make a reconstruction of the results and application in related research possible.