Abstract
We propose a method of estimating a bivariate BRDF from a small number of sampled data using compressed sensing. This method aims to estimate the reflectance of various materials by using the representation space that keeps local information when restored by compressed sensing. We conducted simulated measurements using randomly sampled data and data sampled according to the camera position and orientation, and confirmed that most of the BRDF was successfully restored from 40% sampled data in the case of simulated measurement using a camera and markers.
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Otani, H., Komuro, T., Yamamoto, S., & Tsumura, N. (2019). Bivariate BRDF Estimation Based on Compressed Sensing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11542 LNCS, pp. 483–489). Springer Verlag. https://doi.org/10.1007/978-3-030-22514-8_48
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