Low Latency And Low-Level Sensor Fusion For Automotive Use-Cases
Matthias Pollach,Felix Schiegg,Alois Knoll,Matthias Pollach,Felix Schiegg,Alois Knoll
This work proposes a probabilistic low level automotive sensor fusion approach using LiDAR, RADAR and camera data. The method is stateless and directly operates on associated data from all sensor modalities. Tracking is not used, in order to reduce the object detection latency and create existence hypotheses per frame. The probabilistic fusion uses input from 3D and 2D space. An association method...
