A Multi Sensor Real-time Tracking with LiDAR and Camera

Self driving cars are equipped with various driver-assistive technologies (ADAS) like Forward Collision Warning system (FCW), Adaptive Cruise Control and Collision Mitigation by Breaking (CMbB) to ensure safety. Tracking plays an important role in ADAS systems for understanding dynamic environment. This paper proposes 3D multi-target tracking method by following a lean way of implementation using object detection with aim of real time. Object Tracking is an integral part of environment sensing, which enables the vehicle to estimate the surrounding object's trajectories to accomplish motion planning. The advancement in the object detection methodologies benefits greatly when following the tracking by detection approach. The proposed method implemented 2D tracking on camera data and 3D tracking on LiDAR point cloud data. The estimated state from each sensors are fused together to come with a more optimal state of objects present in the surrounding. The multi object tracking performance has evaluated on publicly available KITTI dataset.