|Visual Inertial Odometry with Pentafocal Geometric Constraints
Pyojin Kim, Hyon Lim, and H. Jin Kim*
International Journal of Control, Automation, and Systems, vol. 16, no. 4, pp.1962-1970, 2018
Abstract : "We present the sliding-window monocular visual inertial odometry that is accurate and robust to outliers
by employing a new observation model grounded on the pentafocal geometric constraints. The previous approaches
are dependent on the unknown 3D coordinates of the features to estimate the ego-motion. However, the inaccurate
3D position of the features can lead to poor performance in motion estimation. To overcome these limitations,
we utilize the pentafocal geometry relationship between five images as camera observation model, which makes it
unnecessary to estimate the 3D position of the features. Furthermore, we apply the pentafocal constraints in the
1-point random sample consensus (RANSAC) algorithm to find incorrect feature correspondences. We demonstrate
the effectiveness of the proposed algorithm in two types of experiments: the KITTI driving scene dataset and the
EuRoC micro aerial vehicle (MAV) flying dataset, both qualitatively and quantitatively. It shows more accurate state
estimation performance compared to the well-known stereo visual odometry algorithm and current state-of-the-art
visual inertial odometry methods."
One-point RANSAC, pentafocal geometry, relative pose estimation, visual inertial odometry.