Detection of obstacles on runway using ego-motion compensation and tracking of significant features

This paper proposes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in presence of extraneous features such as tire-marks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical p o w algorithm. Features are tracked from frame to frame so as t o obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.