Simultaneous Estimation of Near IR BRDF and Fine-Scale Surface Geometry
| Autor: | In So Kweon, Srinivasa G. Narasimhan, Gyeongmin Choe |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Surface (mathematics)
Materials science business.industry 010401 analytical chemistry Scale (descriptive set theory) 02 engineering and technology Albedo 01 natural sciences Texture (geology) 0104 chemical sciences Photometric stereo 0202 electrical engineering electronic engineering information engineering Calibration 020201 artificial intelligence & image processing Computer vision Artificial intelligence Bidirectional reflectance distribution function business Structured light Remote sensing |
| Zdroj: | CVPR |
| DOI: | 10.1109/cvpr.2016.269 |
| Popis: | Near-Infrared (NIR) images of most materials exhibit less texture or albedo variations making them beneficial for vision tasks such as intrinsic image decomposition and structured light depth estimation. Understanding the reflectance properties (BRDF) of materials in the NIR wavelength range can be further useful for many photometric methods including shape from shading and inverse rendering. However, even with less albedo variation, many materials e.g. fabrics, leaves, etc. exhibit complex fine-scale surface detail making it hard to accurately estimate BRDF. In this paper, we present an approach to simultaneously estimate NIR BRDF and fine-scale surface details by imaging materials under different IR lighting and viewing directions. This is achieved by an iterative scheme that alternately estimates surface detail and NIR BRDF of materials. Our setup does not require complicated gantries or calibration and we present the first NIR dataset of 100 materials including a variety of fabrics (knits, weaves, cotton, satin, leather), and organic (skin, leaves, jute, trunk, fur) and inorganic materials (plastic, concrete, carpet). The NIR BRDFs measured from material samples are used with a shape-from-shading algorithm to demonstrate fine-scale reconstruction of objects from a single NIR image. |
| Databáze: | OpenAIRE |
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