Light field SLAM based on ray-space projection model

Pose estimation is the key step of simultaneous localization and mapping (SLAM). The relationship between the rays captured by multiple light field cameras can provide more constraints for pose estimation. In this paper, we propose a novel light field SLAM (LF-SLAM) based on ray-space projection model, including visual odometry, optimization, loop closing and mapping. Unlike traditional SLAM, which estimates pose based on point-point correspondence, we firstly utilize ray-space features to initialize camera motion based on light field fundamental matrix. In addition, a ray-ray cost function is presented to optimize camera pose and 3D points. Finally, we exhibit the motion map and 3D reconstruction results from a moving light field camera. Experimental results have verified the effectiveness and robustness of the proposed method.