Results 61 to 70 of about 111 (93)
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Specularities Reduce Ambiguity of Uncalibrated Photometric Stereo
Lecture Notes in Computer Science, 2002Lambertian photometric stereo with uncalibrated light directions and intensities determines the surface normals only up to an invertible linear transformation. We show that if object reflectance is a sum of Lambertian and specular terms, the ambiguity reduces into a 2dof group of transformations (compositions of isotropic scaling, rotation around the ...
Ondřej Drbohlav +2 more
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Shadow-aware Uncalibrated Photometric Stereo Network
2022 14th International Conference on Computer and Automation Engineering (ICCAE), 2022Yingming Wang +2 more
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A New Perspective on Uncalibrated Photometric Stereo [PDF]
We investigate the problem of reconstructing normals, albedo and lights of Lambertian surfaces in uncalibrated photometric stereo under the perspective projection model. Our analysis is based on establishing the integrability constraint. In the orthographic projection case, it is well-known that when such constraint is imposed, a solution can be ...
Thoma Papadhimitri, Paolo Favaro
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Uncalibrated Photometric Stereo Under Natural Illumination
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018This paper presents a photometric stereo method that works with unknown natural illuminations without any calibration object. To solve this challenging problem, we propose the use of an equivalent directional lighting model for small surface patches consisting of slowly varying normals, and solve each patch up to an arbitrary rotation ambiguity.
Zhipeng Mo +4 more
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Patch-Based Uncalibrated Photometric Stereo Under Natural Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022This paper presents a photometric stereo method that works with unknown natural illumination without any calibration objects or initial guess of the target shape. To solve this challenging problem, we propose the use of an equivalent directional lighting model for small surface patches consisting of slowly varying normals, and solve each patch up to an
Heng Guo 0003 +6 more
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Uncalibrated Photometric Stereo for Unknown Isotropic Reflectances
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances. Our method uses a pixel intensity profile, which is a sequence of radiance intensities recorded at a pixel across multi-illuminance images.
Feng Lu 0005 +4 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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A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016Classic photometric stereo is often extended to deal with real-world materials and work with unknown lighting conditions for practicability. To quantitatively evaluate non-Lambertian and uncalibrated photometric stereo, a photometric stereo image dataset containing objects of various shapes with complex reflectance properties and high-quality ground ...
Boxin Shi, Zhipeng Mo, Sai-Kit Yeung
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Fast 3D face reconstruction based on uncalibrated photometric stereo
Multimedia Tools and Applications, 2013This paper proposes a fast algorithm for three-dimensional face reconstruction using uncalibrated Photometric Stereo. With a reference face model, lighting parameters are estimated from input face images lighted by unknown illumination, which can be used in classical photometric stereo to estimate surface normal and albedo.
Yujuan Sun, Junyu Dong, Muwei Jian
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Coplanar light sweep-surface supported uncalibrated photometric stereo
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., 2004Hui Kong +2 more
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