  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.
