Results 161 to 170 of about 153,707 (188)
Improved Visual Inspection through 3D Image Reconstruction of Defects Based on the Photometric Stereo Technique [PDF]
Sensors, 2019 Ke Xu
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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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2010
We propose a novel algorithm for uncalibrated photometric stereo. While most of previous methods rely on various assumptions on scene properties, we exploit constraints in lighting configurations. We first derive an ambiguous reconstruction by requiring lights to lie on a view centered cone.
Zhenglong Zhou, Ping Tan
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We propose a novel algorithm for uncalibrated photometric stereo. While most of previous methods rely on various assumptions on scene properties, we exploit constraints in lighting configurations. We first derive an ambiguous reconstruction by requiring lights to lie on a view centered cone.
Zhenglong Zhou, Ping Tan
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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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Binocular Uncalibrated Photometric Stereo
2006In Uncalibrated Photometric Stereo (UPS), the surface normals and light sources are determined up to a group of ambiguous Generalized Bas-Relief (GBR) transformations. However, it has been shown by previous works to be rather troublesome to solve these ambiguities. In this paper, a framework of Binocular Uncalibrated Photometric Stereo (B-UPS) is given
Hui Kong 0001 +2 more
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Photometric Stereo via Expectation Maximization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010This paper presents a robust and automatic approach to photometric stereo, where the two main components, namely surface normals and visible surfaces, are respectively optimized by Expectation Maximization (EM). A dense set of input images is conveniently captured using a digital video camera while a handheld spotlight is being moved around the target ...
Wu, Tai-Pang, Tang, Chi-Keung
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Conjugate Gradient in Noisy Photometric Stereo
2014<p>This paper discusses the problem of reconstructing the Lambertian surface from noisy three-light source Photometric Stereo. In the continuous image setting the shape recovery process is divided into two steps: an algebraic one (gradient computation) and analytical one (gradient integration).
Ryszard Kozera +1 more
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Mutual illumination photometric stereo. [PDF]
, 2018 Many techniques have been developed in computer vision to recover three-dimensional shape from two-dimensional images. These techniques impose various combinations of assumptions/restrictions of conditions to produce a representation of shape (e.g. surface normals or a height map). Although great progress has been made it is a problem which remains far
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Testing Photometric Stereo Applications
2022 9th International Conference on Dependable Systems and Their Applications (DSA), 2022Ledio Jahaj, Franz Wotawa
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6th International Conference on Image Processing and its Applications, 1997
A novel variant of photometric stereo, termed reflective photometric stereo (RPS), has been presented. RPS exploits differences in intensity measurements captured under direct and reflected illumination to recover surface orientation from pairs of grey level images.
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A novel variant of photometric stereo, termed reflective photometric stereo (RPS), has been presented. RPS exploits differences in intensity measurements captured under direct and reflected illumination to recover surface orientation from pairs of grey level images.
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