1 / 1

Acquisition of Multispectral Bidirectional Reflectance Distribution Functions

Acquisition of Multispectral Bidirectional Reflectance Distribution Functions. Colin Braley, Jason Lawrence University of Virginia. Background. Setup. BRDF Basics. We take many images of a spherical material sample as a light source moves around a 180 degree arc.

stu
Download Presentation

Acquisition of Multispectral Bidirectional Reflectance Distribution Functions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Acquisition of Multispectral Bidirectional Reflectance Distribution Functions Colin Braley, Jason Lawrence University of Virginia Background Setup BRDF Basics We take many images of a spherical material sample as a light source moves around a 180 degree arc. A BRDF describes how an opaque material reflects light. BRDFs are used in computer graphics to model the appearance of virtual objects. For a ray of light arriving in the direction ωi, the BRDF tells us how much light is reflected back in direction ωo. In general, a BRDF is a 5 dimensional function. We consider the more common isotopic BRDF, which is a function of 4 variables. Measured BRDFs of real world materials allow users in areas such as visual effects and architecture to create highly realistic images of virtual worlds. 12 bit QImagingRetiga 4000R CCD camera Varispec VISLiquid Crystal Tunable Filter Our camera is equipped with a Liquid Crystal Tunable Filter(LCTF) to selectively choose which wavelengths to allow into the camera. Images of Isotropic BRDFsfrom the MERL BRDF Database [1] Top View Calibration For calibration, we have to measure the following: 1) Spectral transmission of our camera and LCTF 2) Spatial sensitivity of our camera 3) Spectrum of our light source Spectral Rendering Humans posses tristimulus vision. As a result of this remarkable property, the sensation of color is describable by only 3 numbers. The RGB colorspace is one such description. Computer graphics software aims to simulate the behavior of light to generate synthetic images. Commonly this simulation is done on RGB colors. This is incorrect, and a full spectral simulation should be used. Conversion to RGB images for human viewing should be a final step. Spectral Transmission Spatial Sensitivity RGB Rendering Spectral Reconstruction Given 30 spectral measurements, we need to reconstruct the underlying spectrum. Fully Spectral Rendering Goal Our goal is to measure the spectral BRDFs of many real world materials. Available BRDF data is sparsely sampled in either the spectral or spatial domain. We hope to produce the first database of many multispectral BRDFs, with dense sampling in both the spatial and angular domains. We use an image based technique, first proposed by Marschner et al[2]. This allows us to take images of spherical targets, and convert each pixel into a measurement. This reduces acquisition time, as multiple measurements are captured in parallel. Related Work 1 - "A Data-Driven Reflectance Model", WojciechMatusik et al., ACM Transactions on Graphics 22, 3(2003), 759-769. 2 – “Image-based BRDF Measurement” Stephen R. Marschner et al. Applied Optics, vol. 39, no. 16 (2000).

More Related