Making Optic Flow Robust to Dynamic Lighting Conditions for Real Time Operation
Abstract Existing optical based state estimation algorithms fail to adequately handle dynamic lighting changes ubiquitous in outdoor environments. To overcome this shortfall, we propose a novel approach that is applicable to all optic flow algorithms, allowing them to operate in dynamic lighting conditions at operational tempos. We posit that the use of a preprocessing filter based on the double derivative of the image will substantially reduce the instability caused by dynamic lighting conditions and improve the overall accuracy of position estimates without a substantial loss of information. Our preprocessing step does not significantly add to the computational cost and requires no a priori knowledge of the environment. In this report, we compare the results of optic flow with and without use of the filter, showing that the former yields a significant improvement in position estimation accuracy as compared to optic flow calculations carried out with a standard input. Preliminary experiments demonstrate the potential of the proposed methodology.