Reflectance and texture of real-world surfaces

Dana, Kristin; Nayar, Shree K.; Ginneken, Bram van; Koenderink, Jan J.

doi:10.1109/cvpr.1997.609313

Cited by 567 publications

(774 citation statements)

References 19 publications

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“…Since their introduction in [Dana et al 1997], several acquisition setups have been proposed to capture BTF data. The BTF, which is an image-based representation of the surface appearance, can also be thought of as a large stack of view-and light-dependent textures.…”

Section: Acquisitionmentioning

confidence: 99%

See 1 more Smart Citation

WebGL-based streaming and presentation of objects with bidirectional texture functions

Schwartz

Ruiters

Weinmann

et al. 2013

J. Comput. Cult. Herit.

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Museums and Cultural Heritage institutions have a growing interest in presenting their collections to a broader community via the Internet. The photo-realistic presentation of interactively inspectable virtual surrogates is one of the most challenging problems in this field. For this purpose, we seek to employ not only a 3D geometry but also a powerful material representation capable of reproducing the full visual appeal of an object. In this paper, we propose a WebGL-based presentation framework in which reflectance information is represented via Bidirectional Texture Functions. Our approach works out-of-the-box in modern web browsers and allows for the progressive transmission and interactive rendering of digitized artifacts consisting of 3D geometry and reflectance information. We handle the huge amount of data needed for this representation by employing a novel progressive streaming approach for BTFs which allows for the smooth interactive inspection of a steadily improving version during the download. We demonstrate an interesting use-case of this technique at a cross-section of Cultural Heritage, medical education and research and provide an evaluation of the capabilities of our framework in the scope of BTF compression and transmission.

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Section: Acquisitionmentioning

confidence: 99%

“…The Bidirectional Texture Function [Dana et al 1997] is a technique which combines the advantages of SLFs and PTMs. A BTF ρ(x, ω i , ω o ) is a function describing the appearance at each point x on a 3D surface, depending on both light-direction ω i and view-direction ω o .…”

Section: Previous Work In Presentation and Dissemination Over The Intmentioning

confidence: 99%

WebGL-based streaming and presentation of objects with bidirectional texture functions

Schwartz

Ruiters

Weinmann

et al. 2013

J. Comput. Cult. Herit.

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“…The appearance of 3D textures has been modeled in [6]. Figure 8 shows the appearance of a rooftop with ridges at different times of the day.…”

Section: Variation In Illuminationmentioning

confidence: 99%

“…The color constancy dataset collected by Funt et al [5] provides a large set of images of objects (boxes, books and so on) acquired under different poses and with different illuminants (fluorescent, halogen, etc). The CURET database [6] provides a set of 12000 images of real world textures under 200 illumination and viewing configurations. It also provides an additional set of 14000 Bi-directional Texture Function (BTF) measurements of 61 real world surfaces.…”

Section: Variability In Scene Appearancementioning

confidence: 99%

All the Images of an Outdoor Scene

Narasimhan

Wang

Nayar

2002

Lecture Notes in Computer Science

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Abstract. The appearance of an outdoor scene depends on a variety of factors such as viewing geometry, scene structure and reflectance (BRDF or BTF), illumination (sun, moon, stars, street lamps), atmospheric condition (clear air, fog, rain) and weathering (or aging) of materials. Over time, these factors change, altering the way a scene appears. A large set of images is required to study the entire variability in scene appearance. In this paper, we present a database of high quality registered and calibrated images of a fixed outdoor scene captured every hour for over 5 months. The dataset covers a wide range of daylight and night illumination conditions, weather conditions and seasons. We describe in detail the image acquisition and sensor calibration procedures. The images are tagged with a variety of ground truth data such as weather and illumination conditions and actual scene depths. This database has potential implications for vision, graphics, image processing and atmospheric sciences and can be a testbed for many algorithms. We describe an example application -image analysis in bad weather -and show how this method can be evaluated using the images in the database. The database is available online at http://www.cs.columbia.edu/CAVE/. The data collection is ongoing and we plan to acquire images for one year. Variability in Scene AppearanceThe appearance of a fixed scene depends on several factors -the viewing geometry, illumination geometry and spectrum, scene structure and reflectance (BRDF or BTF) and the medium (say, atmosphere) in which the scene is immersed. The estimation of one or more of these appearance parameters from one or more images of the scene has been an important part of research in computer vision. Several researchers have focused on solving this inverse problem under specific conditions of illumination (constant or smoothly varying), scene structure (no discontinuities), BRDF (lambertian) and transparent media (pure air). Images captured to evaluate their methods adhere to the specific conditions. While understanding each of these specific cases is important, modeling scene appearance in the most general setting is ultimately the goal of a vision system. To model, develop and evaluate such a general vision system, it is critical to collect a comprehensive set of images that describes the complete variability in the appearance of a scene. Several research groups have collected images of a scene (for example, faces, textures, objects) under varying lighting conditions

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“…Dana et al [7] developed such an equipment for measuring Bidirectional Texture Functions (BTFs). Their system comprised of a robot, lamp, PC, photometer and a video camera.…”

Section: Gonioreflectometersmentioning

confidence: 99%

BRDF Acquisition with Basis Illumination

Ghosh

Achutha

Heidrich

et al. 2007

2007 IEEE 11th International Conference on Computer Vision

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To create a realistic image we need to characterize how light reflects off a surface.In optics terminology, the complete Bidirectional Reflectance Distribution Function is needed. At a given point on a surface the BRDF is a function of two directions, one toward the light and one toward the viewer. Any device for measuring the 4D reflectance data has to obtain measurements over the hemisphere of incident and exitant directions which can be quite tedious if done using the brute-force approach.In this thesis, we describe an efficient image-based acquisition setup that has no moving parts and can acquire reflectance data in a matter of a few minutes. We make this possible by using curved reflective surfaces that eliminate the need to move either the camera or the light source. The acquisition speedup mostly comes from the way we optically sample the BRDF data into a suitable basis. This also saves us the postprocess compression of data. We then encode the data into a compact form that is suitable for use in various rendering systems. ContentsAbstract .

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Reflectance and texture of real-world surfaces

Cited by 567 publications

References 19 publications

WebGL-based streaming and presentation of objects with bidirectional texture functions

WebGL-based streaming and presentation of objects with bidirectional texture functions

All the Images of an Outdoor Scene

BRDF Acquisition with Basis Illumination

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