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Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation

Report No.	ARL-TR-7629
Authors:	Allison Mathis, William Nothwang, Daniel Donavanik, Joseph Conroy, Jared Shamwell, and Ryan Robinson
Date/Pages:	March 2016; 22 pages
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.
Distribution:	Approved for public release
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Last Update / Reviewed: March 1, 2016