1. Introduction
Many 3D computer vision tasks require a robust and reliable understanding of position and orientation in space and a outlier-free localization of the camera with respect to its surroundings is a fundamental requirement in machine vision tasks such as registration, reconstruction or tele-robotics. Independent on the given data modality, the natural underlying structure of the input is a temporally ordered set which can be analyzed sequentially. In an example scenario such as SLAM, egocentric vision or marker tracking, a single camera provides a stream of consecutive images generating a pose path. In this paper, we address motion smoothing, where - given the per frame motion estimates - the goal is to synthesize a new camera trajectory, which is smooth and closer to the underlying movement or intended trajectory.