General Appearance Capture
This research investigates the theoretical and practical aspects of acquiring digital models of the appearance of physical objects. This includes capturing both their 3D shape (geometry) along with the directionally- and spatially-varying functions that characterize the way light is scattered at their surface (reflectance). Some of our recent work explores novel optical arrangements of programmable lights (i.e., digital projectors) and digital cameras to achieve more robust and reliable model recovery for notoriously difficult cases such as surfaces that are shiny, translucent, anisotropic, or have very fine geometric details such as fur. Other work explores new surface reconstruction algorithms that rely on identifying points and planes of partial symmetry within single-view/multi-light datasets. We have shown that these features allow directly estimating the surface gradient (normal field) along with the principal direction of light scattering (tangent field) for a wider range of surfaces and in a more robust way than existing methods. Our group operates a light measurement laboratory to support this research that contains a computer controlled 4-axis spherical gantry along with various cameras, projectors, light sources, and optical equipment. This research is partially supported by the National Science Foundation through a CAREER grant CCF-0747220 ("The Inverse Shade Tree Framework for Material Acquisition, Analysis, and Design") and grant CCF-0811493 ("A Scanning Pipeline for the Synchronous Capture of Precise 3D Shape and Surface Appearance”).
- An Analysis of Using High-Frequency Sinusoidal Illumination for Measuring the 3D Shape of Translucent Objects, Michael Holroyd, Jason Lawrence IEEE Conference on Computer Vision and Pattern Recognition, 2011.
- A Coaxial Optical Scanner for Synchronous Acquisition of 3D Geometry and Surface Reflectance, Michael Holroyd, Jason Lawrence, and Todd Zickler (Proc. SIGGRAPH), 29(4), July 2010.
- Principles of Appearance Acquisition and Representation, Tim Weyrich, Jason Lawrence, Hendrik P. A. Lensch, Szymon Rusinkiewicz, Todd Zickler. In Foundations and Trends in Computer Graphics and Vision, Vol. 4, No. 2, pp. 75-191, 2008 (appeared in 2009).
- A Photometric Approach for Estimating Normals and Tangents, Michael Holroyd, Jason Lawrence, Greg Humphreys, and Todd Zickler, ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 27(5), December 2008.