Objective: Label ground truth data in a video or sequence of images interactively. Automate the labeling with detection and tracking algorithms.

• Overview of Ground Truth Labeler
• Label ROIs (Regions of Interest) and scenes
• Automate labeling
• View/export ground truth results

Objective: Visualize camera frames, radar and lidar detections. Use appropriate coordinate systems to transform image coordinates to vehicle coordinates and vice versa.

• Create bird’s eye plot
• Plot sensor coverage areas
• Visualize detections and lanes
• Convert from vehicle to image coordinates
• Annotate video with detections and lane boundaries

Objective: Segment and model parabolic lane boundaries. Use pretrained object detectors to detect vehicles.

• Perform bird’s eye view transform
• Detect lane features
• Compute lane model
• Validate lane detection with ground truth
• Detect vehicles with pretrained object detectors

Objective: Create a multi-object tracker to fuse information from multiple sensors such as camera, radar etc.

• Track multiple objects
• Preprocess detections
• Kalman filters
• Manage multiple tracks
• Track with multi-object tracker

Objective: Create driving scenarios and synthetic radar/camera sensor detections interactively to test automated driving perception algorithms.

• Overview of Driving Scenario Designer
• Create scenarios with roads, actors and sensors
• Simulate and visualize scenario
• Generate detections and export scenarios
• Test algorithms with scenarios