Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications
This addresses calibration challenges for autonomous driving systems in urban settings, but it is incremental as it builds on existing methods using traffic signs.
The paper tackles the problem of sensor calibration for intelligent vehicles in natural environments by using stop signs as known-shape objects to recalibrate cameras, resulting in convergence and improved performance as demonstrated in real-world tests.
Calibration of sensors is fundamental to robust performance for intelligent vehicles. In natural environments, disturbances can easily challenge calibration. One possibility is to use natural objects of known shape to recalibrate sensors. An approach based on recognition of traffic signs, such as stop signs, and use of them for recalibration of cameras is presented. The approach is based on detection, geometry estimation, calibration, and recursive updating. Results from natural environments are presented that clearly show convergence and improved performance.