Homography-Based Planar Mapping and Tracking for Mobile Phones

We present a real-time camera pose tracking and mapping system which uses the assumption of a planar scene to implement a highly efficient mapping algorithm. Our light-weight mapping approach is based on key frames and plane-induced homographies between them. We solve the planar reconstruction problem of estimating the keyframe poses with an efficient image rectification algorithm. Camera pose tracking uses continuously extended and refined planar point maps and delivers robustly estimated 6DOF poses. We compare system and method with bundle adjustment and monocular SLAM on synthetic and indoor image sequences. We demonstrate large savings in computational effort compared to the monocular SLAM system while the reduction in accuracy remains acceptable.