118898 20240319081003.0 doi 10.1145/3528223.3530075 sideral 130307 ART-2022-130307 eng Hwang, I. Sparse ellipsometry: portable acquisition of polarimetric SVBRDF and shape with unstructured flash photography 2022 Access copy available to the general public Unrestricted Ellipsometry techniques allow to measure polarization information of materials, requiring precise rotations of optical components with different configurations of lights and sensors. This results in cumbersome capture devices, carefully calibrated in lab conditions, and in very long acquisition times, usually in the order of a few days per object. Recent techniques allow to capture polarimetric spatially-varying reflectance information, but limited to a single view, or to cover all view directions, but limited to spherical objects made of a single homogeneous material. We present sparse ellipsometry, a portable polarimetric acquisition method that captures both polarimetric SVBRDF and 3D shape simultaneously. Our handheld device consists of off-the-shelf, fixed optical components. Instead of days, the total acquisition time varies between twenty and thirty minutes per object. We develop a complete polarimetric SVBRDF model that includes diffuse and specular components, as well as single scattering, and devise a novel polarimetric inverse rendering algorithm with data augmentation of specular reflection samples via generative modeling. Our results show a strong agreement with a recent ground-truth dataset of captured polarimetric BRDFs of real-world objects. info:eu-repo/grantAgreement/ES/DGA/LMP30-21 info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON info:eu-repo/grantAgreement/ES/MICINN/PID2019-105004GB-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 6.2 2022 COMPUTER SCIENCE, SOFTWARE ENGINEERING 11 / 108 = 0.102 2022 Q1 T1 3.697 2022 Computer Graphics and Computer-Aided Design 2022 Q1 14.9 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Jeon, D. S. Muñoz, A. Universidad de Zaragoza (orcid)0000-0002-8160-7159 Gutiérrez, D. Universidad de Zaragoza (orcid)0000-0002-7503-7022 Tong, X. Kim, M. H. 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 41, 4 (2022), 133 [14 pp.] ACM trans. graph. ACM TRANSACTIONS ON GRAPHICS 0730-0301 9260143 http://zaguan.unizar.es/record/118898/files/texto_completo.pdf Versión publicada 2609520 http://zaguan.unizar.es/record/118898/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:118898 articulos driver 2024-03-18-14:20:03 ARTICLE