Using vanishing points to improve visual-inertial odometry

This work presents a method for increasing the accuracy of standard visual inertial odometry (VIO) by effectively removing the angular drift that naturally occurs in feature-based VIO. In order to eliminate such drift, we propose to leverage the predominance of parallel lines in man-made environments by using the intersection of their image projections, known as vanishing points (VPs). First, an efficient inertial-based method is presented that accurately and efficiently detects such points. Second, a strategy to deal with these measurements within the framework of an EKF-based VIO system is presented. Furthermore, special care is taken in order to ensure the real-time execution of the estimator in order to comply with time-critical applications running on computationally constrained platforms. Experiments are performed in a mobile device on challenging environments and evaluated against the same VIO system without the use of VPs, demonstrating the superior accuracy when employing the proposed framework.