Gradient and curvature from the photometric-stereo method, including local confidence estimation
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TLDR
In this paper, a 3D shape determination method for full-frame video data at near-video-frame rates (i.e., 15 Hz) is described. But the method is not suitable for the detection of cast shadows and interreflection.Abstract:
The photometric-stereo method is one technique for three-dimensional shape determination that has been implemented in a variety of experimental settings and that has produced consistently good results. The idea is to use intensity values recorded from multiple images obtained from the same viewpoint but under different conditions of illumination. The resulting radiometric constraint makes it possible to obtain local estimates of both surface orientation and surface curvature without requiring either global smoothness assumptions or prior image segmentation. Photometric stereo is moved one step closer to practical possibility by a description of an experimental setting in which surface gradient estimation is achieved on full-frame video data at near-video-frame rates (i.e., 15 Hz). The implementation uses commercially available hardware. Reflectance is modeled empirically with measurements obtained from a calibration sphere. Estimation of the gradient (p, q) requires only simple table lookup. Curvature estimation additionally uses the reflectance map R(p, q). The required lookup table and reflectance maps are derived during calibration. Because reflectance is modeled empirically, no prior physical model of the reflectance characteristics of the objects to be analyzed is assumed. At the same time, if a good physical model is available, it can be retrofitted to the method for implementation purposes. Photometric stereo is subject to error in the presence of cast shadows and interreflection. No purely local technique can succeed because these phenomena are inherently nonlocal. Nevertheless, it is demonstrated that one can exploit the redundancy in three-light-source photometric stereo to detect locally, in most cases, the presence of cast shadows and interreflection. Detection is facilitated by the explicit inclusion of a local confidence estimate in the lookup table used for gradient estimation.read more
Citations
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Journal ArticleDOI
Example-based photometric stereo: shape reconstruction with general, varying BRDFs
Aaron Hertzmann,Steven M. Seitz +1 more
TL;DR: This paper presents a technique for computing the geometry of objects with general reflectance properties from images that can handle objects with arbitrary and spatially-varying BRDFs.
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The 4-source photometric stereo technique for three-dimensional surfaces in the presence of highlights and shadows
S. Barsky,Maria Petrou +1 more
TL;DR: An algorithm for separating the local gradient information and Lambertian color by using 4-source color photometric stereo in the presence of highlights and shadows is presented.
Proceedings ArticleDOI
Retrographic sensing for the measurement of surface texture and shape
TL;DR: A novel device that can be used as a 2.5D “scanner” for acquiring surface texture and shape using a slab of clear elastomer covered with a reflective skin that has no moving parts, uses inexpensive materials, and can be made into a portable device that is used “in the field” to record surface shape and texture.
Proceedings ArticleDOI
Shape estimation in natural illumination
TL;DR: It is demonstrated that many natural lighting environments already have sufficient variability to constrain local shape, and a novel optimization scheme is described that exploits this variability to estimate surface normals from a single image of a diffuse object in natural illumination.
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Depth from shading, defocus, and correspondence using light-field angular coherence
TL;DR: This work develops an improved technique for local shape estimation from defocus and correspondence cues, and shows how shading can be used to further refine the depth, and proposes a new framework that uses angular coherence to optimize depth and shading.
References
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Book
Robot Vision
TL;DR: Robot Vision as discussed by the authors is a broad overview of the field of computer vision, using a consistent notation based on a detailed understanding of the image formation process, which can provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition.
Journal ArticleDOI
Photometric Method For Determining Surface Orientation From Multiple Images
TL;DR: In this paper, a novel technique called photometric stereo is introduced, which is to vary the direction of incident illumination between successive images, while holding the viewing direction constant, and it is shown that this provides sufficient information to determine surface orientation at each image point.
Proceedings Article
Robot vision
TL;DR: A scheme is developed for classifying the types of motion perceived by a humanlike robot and equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented.
Journal ArticleDOI
Three-dimensional object recognition
Paul J. Besl,Ramesh Jain +1 more
TL;DR: In this paper, a precise definition of the 3D object recognition problem is proposed, and basic concepts associated with this problem are discussed, and a review of relevant literature is provided.
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