Representing the light field in finite three-dimensional spaces from sparse discrete samples

Mury, Alexander A.; Pont, Sylvia C.; Koenderink, Jan J.

doi:10.1364/ao.48.000450

Cited by 33 publications

(45 citation statements)

References 17 publications

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“…This is indeed what we found in a subsequent investigation, 6 in which we measured light fields in an empty room under several different types of illumination: the Light Lab (Philips Research). We took plenopter measurements over a regular grid and for any point inside the space enveloped by the measurement points the light field was calculated by means of linear interpolation of the coefficients between the neighbour measurement points.…”

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confidence: 85%

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Ecological optics of natural materials and light fields

Pont

2009

Human Vision and Electronic Imaging XIV

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The appearance of objects in scenes is determined by their shape, material properties and by the light field, and, in contradistinction, the appearance of those objects provides us with cues about the shape, material properties and light field. The latter so-called inverse problem is underdetermined and therefore suffers from interesting ambiguities. Therefore, interactions in the perception of shape, material, and luminous environment are bound to occur.Textures of illuminated rough materials depend strongly on the illumination and viewing directions. Luminance histogram-based measures such as the average luminance, its variance, shadow and highlight modes, and the contrast provide robust estimates with regard to the surface structure and the light field. Human observers performance agrees well with predictions on the basis of such measures. If we also take into account the spatial structure of the texture it is possible to estimate the illumination orientation locally. Image analysis on the basis of second order statistics and human observers estimates correspond well and are both subject to the bas-relief and the convex-concave ambiguities. The systematic robust illuminance flow patterns of local illumination orientation estimates on rough 3D objects are an important entity for shape from shading and for light field estimates. Human observers are able to match and discriminate simple light field properties (e.g. average illumination direction and diffuseness) of objects and scenes, but they make systematic errors, which depend on material properties, object shapes and position in the scene. Moreover, our results show that perception of material and illumination are basically confounded. Detailed analysis of these confounds suggests that observers primarily attend to the low-pass structure of the light field. We measured and visualized this structure, which was found to vary smoothly in natural scenes in-and outdoors.

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“…How do natural scene statistics (e.g. of light fields 5,6 ) constrain these sets? The only formal description of how such combinations result in the same image concerns the bas-relief ambiguity:…”

Section: Introductionmentioning

confidence: 99%

Ecological optics of natural materials and light fields

Pont

2009

Human Vision and Electronic Imaging XIV

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“…The first approach is based on representing the illumination by a large number of spatially distributed angular radiance samples, e.g. a dense grid of light probes [92,146,159,206,208]. The incident light at a point on a synthetic object can then be computed by interpolating the angular radiance distribution of spatially adjacent light probes [138].…”

Section: Previous Approachesmentioning

confidence: 99%

Physically Based Rendering of Synthetic Objects in Real Environments

Kronander¹

2015

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Description of the cover imageRendering of virtual furniture illuminated with spatially varying real world illumination captured in a physical environment at IKEA Communications AB.The virtual scene was modeled by Sören and Per Larsson. Physically based rendering of synthetic objects in real environmentsCopyright © 2015 Joel Kronander (unless otherwise noted) Division of Media and Information TechnologyDepartment of Science and Technology Campus Norrköping, Printed in Sweden by LiU-Tryck, Linköping, 2015 AbstractThis thesis presents methods for photorealistic rendering of virtual objects so that they can be seamlessly composited into images of the real world. To generate predictable and consistent results, we study physically based methods, which simulate how light propagates in a mathematical model of the augmented scene. This computationally challenging problem demands both efficient and accurate simulation of the light transport in the scene, as well as detailed modeling of the geometries, illumination conditions, and material properties. In this thesis, we discuss and formulate the challenges inherent in these steps and present several methods to make the process more efficient.In particular, the material contained in this thesis addresses four closely related areas: HDR imaging, IBL, reflectance modeling, and efficient rendering. The thesis presents a new, statistically motivated algorithm for HDR reconstruction from raw camera data combining demosaicing, denoising, and HDR fusion in a single processing operation. The thesis also presents practical and robust methods for rendering with spatially and temporally varying illumination conditions captured using omnidirectional HDR video. Furthermore, two new parametric BRDF models are proposed for surfaces exhibiting wide angle gloss. Finally, the thesis also presents a physically based light transport algorithm based on Markov Chain Monte Carlo methods that allows approximations to be used in place of exact quantities, while still converging to the exact result. As illustrated in the thesis, the proposed algorithm enables efficient rendering of scenes with glossy transfer and heterogenous participating media.v Populärvetenskaplig SammanfattningEn av de största utmaningarna inom datorgrafik är att syntetisera, eller rendera, fotorealistiska bilder. Fotorealistisk rendering används idag inom många tillämpningsområden såsom specialeffekter i film, datorspel, produktvisualisering och virtuell verklighet. I många praktiska tillämpningar av fotorealistisk rendering är det viktigt att kunna placera in virtuella objekt i fotografier, så att de virtuella objekten ser verkliga ut. IKEA-katalogen, till exempel, produceras i många olika versioner för att passa olika länder och regioner. Grunden till de flesta bilderna i katalogen är oftast densamma, men symboler och standardmått på möbler varierar ofta för olika versioner av katalogen. Istället för att fotografera varje version separat kan man använda ett grundfotografi och lägga in olika virtuella objekt såsom möbler...

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“…It is well known that in order to assign 3-D shape to 2-D shaded images, the human visual system relies in part on an assumption that light comes from overhead, as it does in most real world scenes [1][2][3]. Given the importance of lighting in image formation, recent work has focused on what additional statistical regularities are present in natural lighting [4][5][6][7][8][9], and what assumptions the human visual system makes about lighting [10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

The role of natural lighting diffuseness in human visual perception

Morgenstern

Geisler

Murray

2015

Human Vision and Electronic Imaging XX

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The pattern of the light that falls on the retina is a conflation of real-world sources such as illumination and reflectance. Human observers often contend with the inherent ambiguity of the underlying sources by making assumptions about what real-world sources are most likely. Here we examine whether the visual system's assumptions about illumination match the statistical regularities of the real world. We used a custom-built multidirectional photometer to capture lighting relevant to the shading of Lambertian surfaces in hundreds of real-world scenes. We quantify the diffuseness of these lighting measurements, and compare them to previous biases in human visual perception. We find that (1) natural lighting diffuseness falls over the same range as previous psychophysical estimates of the visual system's assumptions on diffuseness, and (2) natural lighting almost always provides lighting direction cues that are strong enough to override the human visual system's well known assumption that light tends to come from above. A consequence of these findings is that what seem to be errors in visual perception are often actually byproducts of the visual system knowing about and using reliable properties of real-world lighting when contending with ambiguous retinal images.

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Representing the light field in finite three-dimensional spaces from sparse discrete samples

Cited by 33 publications

References 17 publications

Ecological optics of natural materials and light fields

Ecological optics of natural materials and light fields

Physically Based Rendering of Synthetic Objects in Real Environments

The role of natural lighting diffuseness in human visual perception

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