Monocular Direct Sparse Localization in a Prior 3D Surfel Map
This work addresses camera localization for robotics or AR/VR applications, presenting an incremental improvement by integrating global constraints into a direct sparse method.
The paper tackles monocular camera pose tracking in a prior 3D surfel map by using rendered vertex and normal maps to incorporate global planar information into direct photometric error optimization, achieving accurate 6-DoF pose estimation with absolute scale in simulations and real-world experiments.
In this paper, we introduce an approach to tracking the pose of a monocular camera in a prior surfel map. By rendering vertex and normal maps from the prior surfel map, the global planar information for the sparse tracked points in the image frame is obtained. The tracked points with and without the global planar information involve both global and local constraints of frames to the system. Our approach formulates all constraints in the form of direct photometric errors within a local window of the frames. The final optimization utilizes these constraints to provide the accurate estimation of global 6-DoF camera poses with the absolute scale. The extensive simulation and real-world experiments demonstrate that our monocular method can provide accurate camera localization results under various conditions.