Given an image sequence and odometry from a moving camera, we propose a batch-based approach for robust reconstruction of scene structure and camera motion. A key part of our method is robust loop closure disambiguation. First, a structure-from-motion pipeline is used to get a set of candidate feature correspondences and the respective triangulated 3D landmarks. Thereafter, the compatibility of each correspondence constraint and the odometry is evaluated in a bundle-adjustment optimization, where only compatible constraints affect. Our approach is evaluated using data from a Google Tango device. The results show that it produces better reconstructions than the device's built-in software or a state-of-the-art pose-graph formulation.
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