Multi-Depth Cross-Calibration of Gaze Tracker and LiDAR Systems
- Resource Type
- Conference
- Authors
- Heidari, Farzan; Dalirani, Farhad; Rahman, Taufiq; Cheema, Daniel Singh; Bauer, Michael A.
- Source
- 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) Intelligent Transportation Systems (ITSC), 2023 IEEE 26th International Conference on. :1699-1705 Sep, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Space vehicles
Visualization
Laser radar
Three-dimensional displays
Transforms
Sparse matrices
Vehicles
- Language
- ISSN
- 2153-0017
Discovering where a driver looks and what they look at while driving can provide many benefits to improve driving safety in Advanced Driver Assistance Systems (ADAS). Toward this goal, we utilized a research vehicle equipped with a remote gaze tracker installed inside the vehicle and facing the driver and a LiDAR mounted on the roof of the vehicle. We introduce a novel approach for the cross-calibration of the gaze tracker with the LiDAR's system. We also propose a method to estimate the driver's Point of Gaze in the sparse LiDAR point cloud. In order to provide more information about the driver's attention, we introduce a technique to calculate the driver's visual attention area in the 3D space. We empirically demonstrate that our proposed multi-depth calibration-calibration approach yields excellent results to find the transformation matrix between a remote gaze tracker and LiDAR coordinate systems.