Applying Shape from Lighting Variation to Bump Map Capture

Rushmeier, Holly; Taubin, Gabriel; Guéziec, André

doi:10.1007/978-3-7091-6858-5_4

Cited by 84 publications

(72 citation statements)

References 5 publications

(2 reference statements)

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“…Rushmeier et al [10] used a similar, 5-light approach. They proposed a PST system where the highest and lowest values in five components are discarded to avoid highlights and shadows, using the three middle intensities to reconstruct surface normals.…”

Section: Related Workmentioning

confidence: 99%

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Robust estimation of surface properties and interpolation of shadow/specularity components

Drew

Hel-Or

Malzbender

et al. 2012

Image and Vision Computing

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The Polynomial Texture Map framework (PTM) extends the simple model of image formation from the Lambertian variant of Photometric Stereo (PST) to more general reflectances and to more complex-shaped surfaces. It forms an alternative method for apprehending object colour, albedo, and surface normals. Here we consider solving such a model in a robust version, not to date attempted for PTM, with the upshot that both shadows and specularities are identified automatically without the need for any thresholds. Instead of the linear model used in few-source PST for Lambertian surfaces, PTM adopts a higher degree polynomial model. PTM has two aims: interpolation of images for new lighting directions, and recovery of surface properties. Here we show that a robust approach is a good deal more accurate in recovering surface properties. For new-lighting interpolation, we demonstrate that a simple radial basis function interpolation can accurately interpolate specularities as well as attached and cast shadows even with a medium-sized image set, with no need for reflectance sharing across pixels or extremely large numbers of interpolation coefficients.

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Section: Related Workmentioning

confidence: 99%

“…Unlike [10], they argued that simply discarding highest or lowest intensity pixels may lead to information loss so they discard only pixels with doubtful intensities. As extra lights are better, [15] uses a spherical device to capture 156 images.…”

Section: Related Workmentioning

confidence: 99%

Robust estimation of surface properties and interpolation of shadow/specularity components

Drew

Hel-Or

Malzbender

et al. 2012

Image and Vision Computing

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“…Several techniques have been introduced specifically for recovering small-scale surface details, in the form of relief (height) maps or normal maps, assuming various types of materials [2][3][4][5]. The majority of these methods requires a specialized hardware setup [6][7][8][9][10], have long acquisition/processing times [11,12] or are not able to scan specular surfaces [2,3].…”

Section: Fine-scale Geometrymentioning

confidence: 99%

“…The majority of these methods requires a specialized hardware setup [6][7][8][9][10], have long acquisition/processing times [11,12] or are not able to scan specular surfaces [2,3]. In our work we will use a slightly adapted version of the Gray code based approach of Francken et al [1], employing a screen-camera setup as acquistion setup.…”

Section: Fine-scale Geometrymentioning

confidence: 99%

Gloss and Normal Map Acquisition of Mesostructures Using Gray Codes

Francken

Cuypers

Mertens

et al. 2009

Advances in Visual Computing

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Abstract. We propose a technique for gloss and normal map acquisition of finescale specular surface details, or mesostructure. Our main goal is to provide an efficient, easily applicable, but sufficiently accurate method to acquire mesostructures. We therefore employ a setup consisting of inexpensive and accessible components, including a regular computer screen and a digital still camera. We extend the Gray code based normal map acquisition approach of Francken et al. [1] which utilizes a similar setup. The quality of the original method is retained and without requiring any extra input data we are able to extract per pixel glossiness information. In the paper we show the theoretical background of the method as well as results on real-world specular mesostructures.

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“…Rushmeier et al estimate diffuse albedo and normal map from photographs with varied incident light directions [35,3]. A linear light source is employed by Gardner et al [12] to estimate BRDF properties and surface normal.…”

Section: Image-based Reflectance Estimationmentioning

confidence: 99%

Video-based Capturing and Rendering of People

2008

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Abstract. The interesting combination of Chapters in this book gives a nice overview of the importance of the analysis of human motion in three different scientific disciplines, computer vision, biomechanics, and computer graphics. In the computer vision field the main goal has been to develop robust and efficient techniques for capturing and measuring human motion. Researchers from biomechanics, on the other hand, try to capitalize on such measurement methods to analyze the characteristics of human motion. In contrast, the focus of computer graphics research has been to realistically animate and render moving humans. In this Chapter, we will outline that a joint solution to the acquisition, the reconstruction, and the rendering problem paves the trail for video-based capturing and rendering of people. We present a model-based system to create realistic 3D videos of human actors that puts this idea into practice. Our method enables us to capture human actors with multiple video cameras and to render their performances in real-time from arbitrary novel viewpoints and under arbitrary novel lighting conditions.

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Applying Shape from Lighting Variation to Bump Map Capture

Cited by 84 publications

References 5 publications

Robust estimation of surface properties and interpolation of shadow/specularity components

Robust estimation of surface properties and interpolation of shadow/specularity components

Gloss and Normal Map Acquisition of Mesostructures Using Gray Codes

Video-based Capturing and Rendering of People

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