Chen, Bin; Piovarci, MichalISTA; Wang, Chao; Seidel, Hans-Peter; Didyk, Piotr; Myszkowski, Karol; Serrano, Ana
A good match of material appearance between real-world objects and their digital on-screen representations is critical for many applications such as fabrication, design, and e-commerce. However, faithful appearance reproduction is challenging, especially for complex phenomena, such as gloss. In most cases, the view-dependent nature of gloss and the range of luminance values required for reproducing glossy materials exceeds the current capabilities of display devices. As a result, appearance reproduction poses significant problems even with accurately rendered images. This paper studies the gap between the gloss perceived from real-world objects and their digital counterparts. Based on our psychophysical experiments on a wide range of 3D printed samples and their corresponding photographs, we derive insights on the influence of geometry, illumination, and the display’s brightness and measure the change in gloss appearance due to the display limitations. Our evaluation experiments demonstrate that using the prediction to correct material parameters in a rendering system improves the match of gloss appearance between real objects and their visualization on a display device.
SIGGRAPH Asia 2022 Conference Papers
This work is supported by FWF Lise Meitner (Grant M 3319), European Research Council (project CHAMELEON, Grant no. 682080), Swiss National Science Foundation (Grant no. 200502), and academic gifts from Meta.
SIGGRAPH: Computer Graphics and Interactive Techniques Conference
Daegu, South Korea
2022-12-06 – 2022-12-09
Chen B, Piovarci M, Wang C, et al. Gloss management for consistent reproduction of real and virtual objects. In: SIGGRAPH Asia 2022 Conference Papers. Vol 2022. Association for Computing Machinery; 2022. doi:10.1145/3550469.3555406
Chen, B., Piovarci, M., Wang, C., Seidel, H.-P., Didyk, P., Myszkowski, K., & Serrano, A. (2022). Gloss management for consistent reproduction of real and virtual objects. In SIGGRAPH Asia 2022 Conference Papers (Vol. 2022). Daegu, South Korea: Association for Computing Machinery. https://doi.org/10.1145/3550469.3555406
Chen, Bin, Michael Piovarci, Chao Wang, Hans-Peter Seidel, Piotr Didyk, Karol Myszkowski, and Ana Serrano. “Gloss Management for Consistent Reproduction of Real and Virtual Objects.” In SIGGRAPH Asia 2022 Conference Papers, Vol. 2022. Association for Computing Machinery, 2022. https://doi.org/10.1145/3550469.3555406.
B. Chen et al., “Gloss management for consistent reproduction of real and virtual objects,” in SIGGRAPH Asia 2022 Conference Papers, Daegu, South Korea, 2022, vol. 2022.
Chen B, Piovarci M, Wang C, Seidel H-P, Didyk P, Myszkowski K, Serrano A. 2022. Gloss management for consistent reproduction of real and virtual objects. SIGGRAPH Asia 2022 Conference Papers. SIGGRAPH: Computer Graphics and Interactive Techniques Conference vol. 2022, 35.
Chen, Bin, et al. “Gloss Management for Consistent Reproduction of Real and Virtual Objects.” SIGGRAPH Asia 2022 Conference Papers, vol. 2022, 35, Association for Computing Machinery, 2022, doi:10.1145/3550469.3555406.
All files available under the following license(s):
Creative Commons Attribution 4.0 International Public License (CC-BY 4.0):
2022_ACM_SIGGRAPH_Chen.pdf 28.83 MB