Search Results for author:
Found 4 papers, 2 papers with code
Automated Static Camera Calibration with Intelligent Vehicles
Our method does not require any human interaction with the information recorded by both the infrastructure and the vehicle.
Extrinsic Camera Calibration with Semantic Segmentation
Our approach relies on a coarse initial measurement of the camera pose and builds on lidar sensors mounted on a vehicle with high-precision localization to capture a point cloud of the camera environment.
Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks
Automated vehicles need to not only perceive their environment, but also predict the possible future behavior of all detected traffic participants in order to safely navigate in complex scenarios and avoid critical situations, ranging from merging on highways to crossing urban intersections.
LACI: Low-effort Automatic Calibration of Infrastructure Sensors
While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping field of view (FOV), within this work, a cooperative intelligent vehicle is used as callibration target.
