Results 1  10
of
23
A Coaxial Optical Scanner for Synchronous Acquisition of 3D Geometry and Surface Reflectance A radiometric analysis of projected sinusoidal illumination
"... for opaque surfaces ..."
Transparent and Specular Object Reconstruction
, 2010
"... This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with lambertian reflectance is a wellstudied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems ..."
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This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with lambertian reflectance is a wellstudied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems for acquisition systems. This report reviews and categorizes the literature in this field. Despite tremendous interest in object digitization, the acquisition of digital models of transparent or specular objects is far from being a solved problem. On the other hand, realworld data is in high demand for applications such as object modeling, preservation of historic artifacts and as input to datadriven modeling techniques. With this report we aim at providing a reference for and an introduction to the field of transparent and specular object reconstruction. We describe acquisition approaches for different classes of objects. Transparent objects/phenomena that do not change the straight ray geometry can be found foremost in natural phenomena. Refraction effects are usually small and can be considered negligible for these objects. Phenomena as diverse as fire, smoke, and interstellar nebulae can be modeled using a straight ray model of image formation. Refractive and specular surfaces on the other hand change the straight rays into usually piecewise linear ray paths, adding additional complexity to the reconstruction problem. Translucent objects exhibit significant subsurface scattering effects rendering traditional acquisition approaches unstable. Different classes of techniques have been developed to deal with these problems and good reconstruction results can be achieved with current stateoftheart techniques. However, the approaches are still specialized and targeted at very specific object classes. We classify the existing literature and hope to provide an entry point to this exiting field.
Visibility Subspaces: Uncalibrated Photometric Stereo with Shadows
"... Abstract. Photometric stereo relies on inverting the image formation process, and doing this accurately requires reasoning about the visibility of light sources with respect to each image point. While simple heuristics for shadow detection suffice in some cases, they are susceptible to error. This p ..."
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Abstract. Photometric stereo relies on inverting the image formation process, and doing this accurately requires reasoning about the visibility of light sources with respect to each image point. While simple heuristics for shadow detection suffice in some cases, they are susceptible to error. This paper presents an alternative approach for handling visibility in photometric stereo, one that is suitable for uncalibrated settings where the light directions are not known. A surface imaged under a finite set of light sources can be divided into regions having uniform visibility, and when the surface is Lambertian, these regions generally map to distinct threedimensional illumination subspaces. We show that by identifying these subspaces, we can locate the regions and their visibilities, and in the process identify shadows. The result is an automatic method for uncalibrated Lambertian photometric stereo in the presence of shadows, both cast and attached. 1
A Theory of Differential Photometric Stereo for Unknown Isotropic BRDFs
"... This paper presents a comprehensive theory of photometric surface reconstruction from image derivatives. For unknown isotropic BRDFs, we show that two measurements of spatial and temporal image derivatives, under unknown light sources on a circle, suffice to determine the surface. This result is the ..."
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This paper presents a comprehensive theory of photometric surface reconstruction from image derivatives. For unknown isotropic BRDFs, we show that two measurements of spatial and temporal image derivatives, under unknown light sources on a circle, suffice to determine the surface. This result is the culmination of a series of fundamental observations. First, we discover a photometric invariant that relates image derivatives to the surface geometry, regardless of the form of isotropic BRDF. Next, we show that just two pairs of differential images from unknown light directions suffice to recover surface information from the photometric invariant. This is shown to be equivalent to determining isocontours of constant magnitude of the surface gradient, as well as isocontours of constant depth. Further, we prove that specification of the surface normal at a single point completely determines the surface depth from these isocontours. In addition, we propose practical algorithms that require additional initial or boundary information, but recover depth from lower order derivatives. Our theoretical results are illustrated with several examples on synthetic and real data. 1.
Pocket Reflectometry
"... Figure 1: We capture spatiallyvarying, isotropic reflectance in about half a minute of casual scanning using three simple tools shown on the far left. Rendered results from four captured examples are shown on the right. We present a simple, fast solution for reflectance acquisition using tools that ..."
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Cited by 11 (1 self)
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Figure 1: We capture spatiallyvarying, isotropic reflectance in about half a minute of casual scanning using three simple tools shown on the far left. Rendered results from four captured examples are shown on the right. We present a simple, fast solution for reflectance acquisition using tools that fit into a pocket. Our method captures video of a flat target surface from a fixed video camera lit by a handheld, moving, linear light source. After processing, we obtain an SVBRDF. We introduce a BRDF chart, analogous to a color “checker ” chart, which arranges a set of knownBRDF reference tiles over a small card. A sequence of light responses from the chart tiles as well as from points on the target is captured and matched to reconstruct the target’s appearance. We develop a new algorithm for BRDF reconstruction which works directly on these LDR responses, without knowing the light or camera position, or acquiring HDR lighting. It compensates for spatial
Material Classification using BRDF Slices
"... Figure 1: Capturing a BRDF slice and applying a reflectance model improves material classification. Sample captured image, 1 of 64 ..."
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Figure 1: Capturing a BRDF slice and applying a reflectance model improves material classification. Sample captured image, 1 of 64
A Biquadratic Reflectance Model for Radiometric Image Analysis
"... Radiometric image analysis methods heavily rely on reflectance models. Due to the complexity of real materials, methods based on simple models such as the Lambertian model often suffer from inaccuracy. On the other hand, more advanced models such as the CookTorrance model severely complicate the an ..."
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Radiometric image analysis methods heavily rely on reflectance models. Due to the complexity of real materials, methods based on simple models such as the Lambertian model often suffer from inaccuracy. On the other hand, more advanced models such as the CookTorrance model severely complicate the analysis problem. We tackle this dilemma by focusing on the lowfrequency component of the reflectance. We propose a compact biquadratic reflectance model to represent the reflectance of a broad class of materials precisely in the lowfrequency domain. We validate our model by fitting to both existing parametric models and nonparametric measured data, and show that our model outperforms existing parametric diffuse models. We show applications of reflectometry using general diffuse surfaces and photometric stereo for general isotropic materials. Experimental results show the effectiveness of our biquadratic model and its usefulness in radiometric image analysis. 1.
Multiview photometric stereo with spatially varying isotropic materials
 In CVPR
, 2013
"... We present a method to capture both 3D shape and spatially varying reflectance with a multiview photometric stereo technique that works for general isotropic materials. Our data capture setup is simple, which consists of only a digital camera and a handheld light source. From a single viewpoint, w ..."
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We present a method to capture both 3D shape and spatially varying reflectance with a multiview photometric stereo technique that works for general isotropic materials. Our data capture setup is simple, which consists of only a digital camera and a handheld light source. From a single viewpoint, we use a set of photometric stereo images to identify surface points with the same distance to the camera. We collect this information from multiple viewpoints and combine it with structurefrommotion to obtain a precise reconstruction of the complete 3D shape. The spatially varying isotropic bidirectional reflectance distribution function (BRDF) is captured by simultaneously inferring a set of basis BRDFs and their mixing weights at each surface point. According to our experiments, the captured shapes are accurate to 0.3 millimeters. The captured reflectance has relative rootmeansquare error (RMSE) of 9%. 1.
Acquiring reflectance and shape from continuous spherical harmonic illumination
 ACM Transactions on Graphics (TOG
, 2013
"... diffuse, specular, specular normal, and specular roughness maps. (c) A rendering of the sunglasses with geometry and reflectance derived from the SH illumination and multiview reconstruction. We present a novel technique for acquiring the geometry and spatiallyvarying reflectance properties of 3D o ..."
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Cited by 5 (0 self)
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diffuse, specular, specular normal, and specular roughness maps. (c) A rendering of the sunglasses with geometry and reflectance derived from the SH illumination and multiview reconstruction. We present a novel technique for acquiring the geometry and spatiallyvarying reflectance properties of 3D objects by observing them under continuous spherical harmonic illumination conditions. The technique is general enough to characterize either entirely specular or entirely diffuse materials, or any varying combination across the surface of the object. We employ a novel computational illumination setup consisting of a rotating arc of controllable LEDs which sweep out programmable spheres of incident illumination during 1second exposures. We illuminate the object with a succession of spherical harmonic illumination conditions, as well as photographed environmental lighting for validation. From the response of the object to the harmonics, we can separate diffuse and specular reflections, estimate worldspace diffuse and specular normals, and compute anisotropic roughness parameters for each view of the object. We then use the maps of both diffuse and specular reflectance to form correspondences in a multiview stereo algorithm, which allows even highly specular surfaces to be corresponded across views. The algorithm yields a complete 3D model and a set of merged reflectance maps. We use this technique to digitize the shape and reflectance of a variety of objects difficult to acquire with other techniques and present validation renderings which match well to photographs in similar lighting.
On Differential Photometric Reconstruction for Unknown
"... Abstract—This paper presents a comprehensive theory of photometric surface reconstruction from image derivatives, in the presence of a general, unknown isotropic BRDF. We derive precise topological classes up to which the surface may be determined and specify exact priors for a full geometric recons ..."
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Abstract—This paper presents a comprehensive theory of photometric surface reconstruction from image derivatives, in the presence of a general, unknown isotropic BRDF. We derive precise topological classes up to which the surface may be determined and specify exact priors for a full geometric reconstruction. These results are the culmination of a series of fundamental observations. First, we exploit the linearity of chain rule differentiation to discover photometric invariants that relate image derivatives to the surface geometry, regardless of the form of isotropic BRDF. For the problem of shape from shading, we show that a reconstruction may be performed up to isocontours of constant magnitude of the gradient. For the problem of photometric stereo, we show that just two measurements of spatial and temporal image derivatives, from unknown light directions on a circle, suffice to recover surface information from the photometric invariant. Surprisingly, the form of the invariant bears a striking resemblance to optical flow, however, it does not suffer from the aperture problem. This photometric flow is shown to determine the surface up to isocontours of constant magnitude of the surface gradient, as well as isocontours of constant depth. Further, we prove that specification of the surface normal at a single point completely determines the surface depth from these isocontours. In addition, we propose practical algorithms that require additional initial or boundary information, but recover depth from lower order derivatives. Our theoretical results are illustrated with several examples on synthetic and real data. 1