Fast method of sparse acquisition and reconstruction of view and illumination dependent datasets

• Published in: Computers & graphics 2013-08, Vol.37 (5), p.376-388
• Main Authors: Filip, Jiří, Vávra, Radomír
• Format: Article
• Language: English
• Subjects: Acquisitions; Algorithmics. Computability. Computer arithmetics; Anisotropy; Apparent BRDF; Applied sciences; Approximation; Artificial intelligence; Computer graphics; Computer science; control theory; systems; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Hardware; Illumination; Information, signal and communications theory; Marketing; Measurement; Pattern recognition. Digital image processing. Computational geometry; Portable setup; Reconstruction; Reproduction; Signal and communications theory; Signal, noise; Sparse sampling; Telecommunications and information theory; Theoretical computing
• ISSN: 0097-8493; 1873-7684
• DOI: 10.1016/j.cag.2013.02.010

Although computer graphics uses measured view and illumination dependent data to achieve realistic digital reproduction of real-world material properties, the extent of their utilization is currently limited by a complicated acquisition process. Due to the high dimensionality of such data, the acquisition process is demanding on time and resources. Proposed is a method of approximate reconstruction of the data from a very sparse dataset, obtained quickly using inexpensive hardware. This method does not impose any restrictions on input datasets and can handle anisotropic, non-reciprocal view and illumination direction-dependent data. The method's performance was tested on a number of isotropic and anisotropic apparent BRDFs, and the results were encouraging. The method performs better than the uniform sampling of a comparable sample count and has three main benefits: the sparse data acquisition can be done quickly using inexpensive hardware, the measured material does not need to be extracted or removed from its environment, and the entire process of data reconstruction from the sparse samples is quick and reliable. Finally, the ease of sparse dataset acquisition was verified in measurement experiments with three materials, using a simple setup of a consumer camera and a single LED light. The proposed method has also shown promising performance when applied to sparse measurement and reconstruction of BTFs, mainly for samples with a lower surface height variation. Our approach demonstrates solid performance across a wide range of view and illumination dependent datasets, therefore creating a new opportunity for development of time and cost-effective portable acquisition setups. [Display omitted] •Method for fast and inexpensive acquisition of anisotropic non-reciprocal BRDFs.•Fast and continuous measurement of BRDF slices by a consumer camera and light.•Fast reconstruction of anisotropic BRDFs and BTFs from the measured slices.