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Image-Based Rendering of Diffuse, Specular and Glossy Surfaces from a Single Image. (2001)

by S Boivin, A Gagalowitcz
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Image-Based Reconstruction of Spatial Appearance and Geometric Detail

by Hendrik P. A. Lensch, Jan Kautz, Michael Goesele, Wolfgang Heidrich, Hans-peter Seidel - ACM Transactions on Graphics , 2003
"... ÓÙÖ Ñ��×ÙÖ� � �Ê�� × � ��� � ÕÙ�Ð�ØÝ ÑÓ��Ð Ó � � Ö��Ð Ó�� � Ø �Ò � � ��Ò�Ö�Ø� � Û�Ø � Ö�Ð�Ø�Ú�ÐÝ ..."
Abstract - Cited by 145 (24 self) - Add to MetaCart
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Measuring Bidirectional Texture Reflectance with a Kaleidoscope

by Jefferson Y. Han Ken Perlin - In Proc. SIGGRAPH , 2003
"... We describe a new technique for measuring the bidirectional texture function (BTF) of a surface that requires no mechanical movement, can measure surfaces in situ under arbitrary lighting conditions, and can be made small, portable and inexpensive. The enabling innovation is the use of a tapered kal ..."
Abstract - Cited by 59 (0 self) - Add to MetaCart
We describe a new technique for measuring the bidirectional texture function (BTF) of a surface that requires no mechanical movement, can measure surfaces in situ under arbitrary lighting conditions, and can be made small, portable and inexpensive. The enabling innovation is the use of a tapered kaleidoscope, which allows a camera to view the same surface sample simultaneously from many directions. Similarly, the surface can be simultaneously illuminated from many directions, using only a single structured light source. We describe the techniques of construction and measurement, and we show experimental results.

Seing people in different light: Joint shape, motion and reflectance capture

by Christian Theobalt, Naveed Ahmed, Hendrik Lensch, Marcus Magnor, Hans-peter Seidel - IEEE TVCG
"... Abstract—By means of passive optical motion capture, real people can be authentically animated and photo-realistically textured. To import real-world characters into virtual environments, however, surface reflectance properties must also be known. We describe a video-based modeling approach that cap ..."
Abstract - Cited by 37 (8 self) - Add to MetaCart
Abstract—By means of passive optical motion capture, real people can be authentically animated and photo-realistically textured. To import real-world characters into virtual environments, however, surface reflectance properties must also be known. We describe a video-based modeling approach that captures human shape and motion as well as reflectance characteristics from a handful of synchronized video recordings. The presented method is able to recover spatially varying surface reflectance properties of clothes from multiview video footage. The resulting model description enables us to realistically reproduce the appearance of animated virtual actors under different lighting conditions, as well as to interchange surface attributes among different people, e.g., for virtual dressing. Our contribution can be used to create 3D renditions of real-world people under arbitrary novel lighting conditions on standard graphics hardware. Index Terms—3D video, dynamic reflectometry, real-time rendering, relighting. Ç 1
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...d to reconstruct a reflectance model. Reflectance measurements of scenes with more complex incident illumination can be derived by either a full-blown inverse global illumination approach [37], [12], =-=[4]-=- or by representing the incident light field as an environment map and solving for the direct illumination component only [38], [31], [28]. In our approach, we will approximate the incident illuminati...

Rendering Synthetic Objects into Legacy Photographs

by Kevin Karsch, Varsha Hedau, David Forsyth, Derek Hoiem
"... Figure 1: With only a small amount of user interaction, our system allows objects to be inserted into legacy images so that perspective, occlusion, and lighting of inserted objects adhere to the physical properties of the scene. Our method works with only a single LDR photograph, and no access to th ..."
Abstract - Cited by 33 (3 self) - Add to MetaCart
Figure 1: With only a small amount of user interaction, our system allows objects to be inserted into legacy images so that perspective, occlusion, and lighting of inserted objects adhere to the physical properties of the scene. Our method works with only a single LDR photograph, and no access to the scene is required. We propose a method to realistically insert synthetic objects into existing photographs without requiring access to the scene or any additional scene measurements. With a single image and a small amount of annotation, our method creates a physical model of the scene that is suitable for realistically rendering synthetic objects with diffuse, specular, and even glowing materials while accounting for lighting interactions between the objects and the scene. We demonstrate in a user study that synthetic images produced by our method are confusable with real scenes, even for people who believe they are good at telling the difference. Further, our study shows that our method is competitive with other insertion methods while requiring less scene information. We also collected new illumination and reflectance datasets; renderings produced by our system compare well to ground truth. Our system has applications in the movie and gaming industry, as well as home decorating and user content creation, among others.

Blind reflectometry

by Fabiano Romeiro, Yuriy Vasilyev, Todd Zickler - In ECCV , 2010
"... Abstract. Different materials reflect light in different ways, so reflectance is a useful surface descriptor. Existing systems for measuring reflectance are cumbersome, however, and although the process can be streamlined using cameras, projectors and clever catadioptrics, it generally requires comp ..."
Abstract - Cited by 30 (2 self) - Add to MetaCart
Abstract. Different materials reflect light in different ways, so reflectance is a useful surface descriptor. Existing systems for measuring reflectance are cumbersome, however, and although the process can be streamlined using cameras, projectors and clever catadioptrics, it generally requires complex infrastructure. In this paper we propose a simpler method for inferring reflectance from images, one that eliminates the need for active lighting and exploits natural illumination instead. The method’s distinguishing property is its ability to handle a broad class of isotropic reflectance functions, including those that are neither radially-symmetric nor well-represented by low-parameter reflectance models. The key to the approach is a bi-variate representation of isotropic reflectance that enables a tractable inference algorithm while maintaining generality. The resulting method requires only a camera, a light probe, and as little as one HDR image of a known, curved, homogeneous surface. 1
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... one can exploit them to recover more than just reflectance information from a set of input images. For example, there are methods for handling global illumination effects and anisotropic reflectance =-=[8, 9]-=-, spatial reflectance variation, and the simultaneous recovery of illumination and/or shape (e.g., [10,11]). (Patow et al. [12] provide a review.) Every parametric approach suffers from limited accura...

Reflectance Sharing: Predicting Appearance from a Sparse Set of Images of a Known Shape

by T Zickler, R Ramamoorthi, S Enrique, P N Belhumeur - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2006
"... ..."
Abstract - Cited by 29 (2 self) - Add to MetaCart
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... is known to be less accurate. Despite these limitations, the method obtains reasonable results, and they would be difficult to improve without assuming a specific parametric BRDF model (as in, e.g., =-=[57]-=-). 9 CONCLUSIONS AND FUTURE WORK This paper presents a method for exploiting spatial coherence to estimate a nonparametric, spatially varying reflectance function from a sparse set of images of known ...

A survey of inverse rendering problems

by Gustavo Patow, Xavier Pueyo - COMP. GRAPHICS FORUM , 2003
"... Inverse rendering problems usually represent extremely complex and costly processes, but their importance in many research areas is well known. In particular, they are of extreme importance in lighting engineering, where potentially costly mistakes usually make it unfeasible to test design decisions ..."
Abstract - Cited by 26 (0 self) - Add to MetaCart
Inverse rendering problems usually represent extremely complex and costly processes, but their importance in many research areas is well known. In particular, they are of extreme importance in lighting engineering, where potentially costly mistakes usually make it unfeasible to test design decisions on a model. In this survey we present the main ideas behind these kinds of problems, characterize them, and summarize work developed in the area, revealing problems that remain unsolved and possible areas of further research.
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...lassified according to equation 2. Inverse Lighting (Le) [52], [37], [36], [7], [55], [35] [23],[14], [12], [32], [15], [38] [40], [51], [59],[58],[57] [42],[47],[18] Inverse Reflectometry (K̂ ) [9], =-=[3]-=-, [14], [12], [62], [32], [31], [26], [28], [44], [41], [13], [34], [45, 43], [36, 39], [54], [60], [10], [63], [36], [51] Combined Problems (Le and K̂ ) [29], [51], [58], [59] no inter-reflections, i...

First Steps Toward an Electronic Field Guide for Plants.'' Taxon

by Gaurav Agarwal, Haibin Ling, David Jacobs, Sameer Shirdhonkar, W. John Kress, Rusty Russell, Peter Belhumeur, An Dixit, Steven Feiner, Dhruv Mahajan, Kalyan Sunkavalli, Ravi Ramamoorthi, Sean White , 2006
"... species identification, content-based image retrieval, computer vision, ..."
Abstract - Cited by 25 (8 self) - Add to MetaCart
species identification, content-based image retrieval, computer vision,

Classification of Illumination Methods for Mixed Reality

by Katrien Jacobs, C. Loscos , 2006
"... A mixed reality (MR) represents an environment composed both by real and virtual objects. MR applications are used more and more, for instance in surgery, architecture, cultural heritage, entertainment, etc. For some of these applications it is important to merge the real and virtual elements using ..."
Abstract - Cited by 25 (1 self) - Add to MetaCart
A mixed reality (MR) represents an environment composed both by real and virtual objects. MR applications are used more and more, for instance in surgery, architecture, cultural heritage, entertainment, etc. For some of these applications it is important to merge the real and virtual elements using consistent illumination. This paper proposes a classification of illumination methods for MR applications that aim at generating a merged environment in which illumination and shadows are consistent. Three different illumination methods can be identified: common illumination, relighting and methods based on inverse illumination. In this paper a classification of the illumination methods for MR is given based on their input requirements: the amount of geometry and radiance known of the real environment. This led us to define four categories of methods that vary depending on the type of geometric model used for representing the real scene, and the sdifferent radiance information available for each point of the real scene. Various methods are described within their category. The classification points out that in general the quality of the illumination interactions increases with the amount of input information available. On the other hand, the accessibility of the method decreases since its pre-processing time increases to gather the extra information. Recent developed techniques managed to compensate unknown data with clever techniques using an iterative algorithm, hardware illumination or recent progress in stereovision. Finally, a review of illumination techniques for MR is given with a discussion on important properties such as the possibility of interactivity or the amount of complexity in the simulated illumination.

Recognition of Surface Reflectance Properties from a Single Image under Unknown Real-World Illumination

by Ron O. Dror, Edward H. Adelson, Alan S. Willsky , 2001
"... This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectio ..."
Abstract - Cited by 24 (1 self) - Add to MetaCart
This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of real-world illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.
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