Abstract
Differential Evolution is an optimization technique that has been successfully employed in various applications. In this paper we propose a novel Population Adaptive Differential Evolution strategy to the problem of generating an optimal light configuration for photometric stereo. For ānā lights, any 2Ļ/n of orthogonal light directions minimizes the uncertainty in scaled normal computation. The assumption is that the camera noise is additive and normally distributed. Uncertainty is defined as the expectation of squared distance of scaled normal to the ground truth. This metric is optimized with respect to the illumination angles at constant slant angle. Superiority of the new method is demonstrated by comparing it with sensitivity analysis and classical DE.
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Sathyabama, B., Divya, V., Raju, S., Abhaikumar, V. (2010). A Population Adaptive Differential Evolution Strategy to Light Configuration Optimization of Photometric Stereo. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_6
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DOI: https://doi.org/10.1007/978-3-642-17563-3_6
Publisher Name: Springer, Berlin, Heidelberg
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