Results 81 to 90 of about 158,596 (115)
A Benchmark Dataset and Evaluation for Non-Lambertian and Uncalibrated Photometric Stereo
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Classic 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, Sai-Kit Yeung, Zhipeng Mo
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Revisiting One-Stage Deep Uncalibrated Photometric Stereo via Fourier Embedding
IEEE Transactions on Pattern Analysis and Machine IntelligenceThis paper introduces a one-stage deep uncalibrated photometric stereo (UPS) network, namely Fourier Uncalibrated Photometric Stereo Network (FUPS-Net), for non-Lambertian objects under unknown light directions. It departs from traditional two-stage methods that first explicitly learn lighting information and then estimate surface normals.
Alex Kot, Boxin Shi, Kenneth Lam
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Spin-UP: Spin Light for Natural Light Uncalibrated Photometric Stereo [PDF]
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Paper accepted by ...
Gang Pan, Xudong Jiang, Qian Zheng
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Uncalibrated, Unified and Unsupervised Specular-Aware Photometric Stereo
Lecture Notes in Computer Science, 2023 In this paper we present a variational approach to simultaneously recover the 3D reconstruction, reflectance, lighting and specularities of an object, all of them, from a set of RGB images. The approach works in an uncalibrated, unified and unsupervised manner, without assuming any prior knowledge of the shape geometry or training data to constrain the
Antonio Agudo, Pablo Estévez Grana
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Some of the next articles are maybe not open access.
Uncalibrated Photometric Stereo Using Superquadrics with Cast Shadow
Communications in Computer and Information Science, 2021Formulated as an inverse problem of computer graphics, inverse rendering (or photometric stereo) can estimate parameters, such as the shapes and configurations of objects and light sources in the scene, from a set of images. Such results can be useful for applications including recognition, inspection, and/or VR.
Norikazu Takahashi
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Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation
Communications in Computer and Information Science, 2022Norikazu Takahashi
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Uncalibrated photometric stereo refined by polarization angle
Optical Review, 2021Photometric stereo allows us to estimate the surface normal of an object based on its shading. In uncalibrated photometric stereo, the light source direction is unknown; thus, both the light source direction and surface normal should be estimated, which establishes an ill-posed problem with ambiguity in its solution. Consequently, assumptions should be
Daisuke Miyazaki
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Visibility Subspaces: Uncalibrated Photometric Stereo with Shadows [PDF]
Lecture Notes in Computer Science, 2010 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
Hanspeter Pfister +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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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 ...
Radim Sara, Ondřej Drbohlav
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