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Self-calibrating photometric stereo
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010We present a self-calibrating photometric stereo method. From a set of images taken from a fixed viewpoint under different and unknown lighting conditions, our method automatically determines a radiometric response function and resolves the generalized bas-relief ambiguity for estimating accurate surface normals and albedos.
Boxin Shi +4 more
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Learning to Minify Photometric Stereo
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions. To deal with diverse factors involved in the image formation process, recent photometric stereo methods demand a large number of images as input.
Junxuan Li +3 more
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Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003
An active vision technique for determining the absolute depth of surfaces is described. The algorithm assumes a very general model for the reflectance properties of the surface, and is valid for most of the shading models commonly used in computer vision work.
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An active vision technique for determining the absolute depth of surfaces is described. The algorithm assumes a very general model for the reflectance properties of the surface, and is valid for most of the shading models commonly used in computer vision work.
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An approximation technique for photometric stereo
Pattern Recognition Letters, 1984Photometric stereo is a technique to determine the orientation of an object. It takes at least three images corresponding to three different light sources to determine the orientation and to eliminate the ambiguities which will arise if only two light sources are used.
Chia-Hoang Lee, Azriel Rosenfeld
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ShadowCuts: Photometric Stereo with Shadows
2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007We present an algorithm for performing Lambertian photometric stereo in the presence of shadows. The algorithm has three novel features. First, a fast graph cuts based method is used to estimate per pixel light source visibility. Second, it allows images to be acquired with multiple illuminants, and there can be fewer images than light sources.
Manmohan Krishna Chandraker +2 more
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Deep Photometric Stereo Network
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017This paper presents a photometric stereo method based on deep learning. One of the major difficulties in photometric stereo is designing can appropriate reflectance model that is both capable of representing real-world reflectances and computationally tractable in terms of deriving surface normal. Unlike previous photometric stereo methods that rely on
Hiroaki Santo +4 more
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Recognition of polyhedra by photometric stereo
1989This paper describes an image segmentation and analysis technique based on three-dimensional information gathered by means of the stereo-photometric approach. It allows the measure of the attitude and area of surfaces whose optical properties are known.
Luigi Carrioli, Ugo Cei, Marco Diani
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Resolution-Enhanced Photometric Stereo
2006Conventional photometric stereo has a fundamental limitation that the scale of recovered geometry is limited to the resolution of the input images. However, surfaces that contain sub-pixel geometric structures are not well modelled by a single normal direction per pixel.
Ping Tan 0002 +2 more
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Time‐Lapse Photometric Stereo and Applications
Computer Graphics Forum, 2014AbstractThis paper presents a technique to recover geometry from time‐lapse sequences of outdoor scenes. We build upon photometric stereo techniques to recover approximate shadowing, shading and normal components allowing us to alter the material and normals of the scene. Previous work in analyzing such images has faced two fundamental difficulties: 1.
Fangyang Shen +5 more
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Base Materials for Photometric Stereo
2012Image-based capture of material appearance has been extensively studied, but the quality of the results and generality of the applied methods leave a lot of room for improvement. Most existing methods rely on parametric models of reflectance and require complex hardware systems or accurate geometric models that are not always available or practical ...
David Tingdahl +2 more
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