LaserSupported Monocular Visual Tracking for Natural Environments This paper presents and demonstrates a 2D lasersupported visual tracking solution, that can achieve reliable performance in unstructured scenes such as those seen in natural environment surveys. The method is shown to sufficiently stabilize scale and account for scale drift, as well as improve overall reliability. The suggested method is minimally invasive, does not require any additional parameter and does not necessarily require a laser, which can be replaced by any set of points with known depth, with no constraint on the temporal continuity of known points. We also test our method on 4 surveys, captured in a natural riverine environment, that proved to be challenging even for the stateoftheart in visual tracking.

Multipleobject Tracking based on Monocular Camera and 3D Lidar Fusion for Autonomous Vehicles This article describes a multiobject tracking method through sensor fusion with a monocular camera and a 3D Lidar for autonomous vehicles. Specifically, several pairwise costs from information, such as locations, movements, and poses of 3D cues, are designed for tracking. These costs can complement each other to reduce matching errors during the tracking process. Moreover, they are efficient to be online computed with embedded equipment. We feed the pairwise costs to the dataassociation framework, which is based on the Hungarian algorithm, and then do the backend fusion for the tracking results. The experimental results on our autonomous sightseeing car demonstrate that our tracking method could achieve accurate and robust results in realworld traffic scenarios.