Fast Odometry Integration in Local Bundle Adjustment-Based Visual SLAM

The Simultaneous Localisation And Mapping (SLAM) for a camera moving in a scene is a long term research problem. Here we improve a recent visual SLAM which applies Local Bundle Adjustments (LBA) on selected key-frames of a video: we show how to correct the scale drift observed in long monocular video sequence using an additional odometry sensor. Our method and results are interesting for several reasons: (1) the pose accuracy is improved on real examples (2) we do not sacrifice the consistency between the reconstructed 3D points and image features to fit odometry data (3) the modification of the original visual SLAM method is not difficult.