Accurate And Computationally-Inexpensive Recovery Of Ego-Motion Using Optical Flow And Range Flow With Extended Temporal Support

The ego-motion of a moving RGB-Z sensor is computed using combined range flow and optical flow pixel constraints. The emphasis of the work is on computationally cheap yet accurate estimation of inter-frame translation and rotation parameters using a linear small rotation model. To ensure accurate inter-frame motion estimates, an iterative form of the estimator is developed which repeatedly warps the target frame and measures its misalignment with the current frame. As these motion estimates are integrated temporally, to minimise drift in pose over time, additional temporal constraint is provided through the use of anchor frames. The algorithm is evaluated on the recently published TUB RGB-D Benchmark which also includes a set of standard metrics. Results presented suggest that performance is commensurate with alternative methodologies such as SLAM but at a fraction of the computational cost.