A novel re-tracking strategy for monocular SLAM

Abstract

Tracking failure is an inevitable event in real-time monocular simultaneous localization and mapping (SLAM) system. Relocalization procedure that focuses on exploring a visited place to relocalize a camera is usually used to handle this problem. However, this strategy abandons the poses of the frames captured after tracking failure, resulting in losing a part of trajectory with respect to the ground truth. Therefore, a re-tracking strategy (RTS) is proposed to estimate these abandoned frames. An automatic local initialization is activated to initialize a new tracking process when tracking fails. Trajectory correction and fusion are employed when a loop closure is detected. When the last frame of the sequence is detected, the trajectories that cannot loop with the original trajectory should be culled by trajectory culling procedure. Experimental results on two challenging datasets, TUM RGB-D and NewCollege, indicate that the proposed method achieves low root mean square error (RMSE) and high trajectory completeness rate (TCR), especially for rapid moving camera.