scholarly journals Color Photometric Stereo Using Multi-Band Camera Constrained by Median Filter and Occluding Boundary

2019 ◽  
Vol 5 (7) ◽  
pp. 64 ◽  
Author(s):  
Daisuke Miyazaki ◽  
Yuka Onishi ◽  
Shinsaku Hiura
Keyword(s):  
Median Filter ◽  
Photometric Stereo ◽  
Initial Guess ◽  
Light Sources ◽  
Constraint Condition ◽  
Measurement Device ◽  
Normal Estimation ◽  
Surface Normal ◽  
Abstract Shape ◽  
Object Region

One of the main problems faced by the photometric stereo method is that several measurements are required, as this method needs illumination from light sources from different directions. A solution to this problem is the color photometric stereo method, which conducts one-shot measurements by simultaneously illuminating lights of different wavelengths. However, the classic color photometric stereo method only allows measurements of white objects, while a surface-normal estimation of a multicolored object using this method is theoretically impossible. Therefore, it is necessary to add some constraints to estimate the surface normal of a multicolored object using the framework of the color photometric stereo method. In this study, a median filter is employed as the constraint condition of albedo, and the surface normal of the occluding boundary is employed as the constraint condition of the surface normal. By employing a median filter as the constraint condition, the smooth distribution of the albedo and normal is calculated while the sharp features at the boundary of different albedos and normals are preserved. The surface normal at the occluding boundary is propagated into the inner part of the object region, and forms the abstract shape of the object. Such a surface normal gives a great clue to be used as an initial guess to the surface normal. To demonstrate the effectiveness of this study, a measurement device that can realize the multispectral photometric stereo method with seven colors is employed instead of the classic color photometric stereo method with three colors.

From Intensity Profile to Surface Normal: Photometric Stereo for Unknown Light Sources and Isotropic Reflectances

2015 ◽  
Vol 37 (10) ◽  
pp. 1999-2012 ◽  
Author(s):  
Feng Lu ◽  
Yasuyuki Matsushita ◽  
Imari Sato ◽  
Takahiro Okabe ◽  
Yoichi Sato
Keyword(s):  
Photometric Stereo ◽  
Intensity Profile ◽  
Light Sources ◽  
Surface Normal

scholarly journals Pay Attention to Devils: A Photometric Stereo Network for Better Details

2020 ◽  
Author(s):  
Yakun Ju ◽  
Kin-Man Lam ◽  
Yang Chen ◽  
Lin Qi ◽  
Junyu Dong
Keyword(s):  
Neural Network ◽  
State Of The Art ◽  
Photometric Stereo ◽  
Normal Map ◽  
Surface Normal ◽  
3D Surface ◽  
Surface Reconstructions ◽  
Higher Weights

We present an attention-weighted loss in a photometric stereo neural network to improve 3D surface recovery accuracy in complex-structured areas, such as edges and crinkles, where existing learning-based methods often failed. Instead of using a uniform penalty for all pixels, our method employs the attention-weighted loss learned in a self-supervise manner for each pixel, avoiding blurry reconstruction result in such difficult regions. The network first estimates a surface normal map and an adaptive attention map, and then the latter is used to calculate a pixel-wise attention-weighted loss that focuses on complex regions. In these regions, the attention-weighted loss applies higher weights of the detail-preserving gradient loss to produce clear surface reconstructions. Experiments on real datasets show that our approach significantly outperforms traditional photometric stereo algorithms and state-of-the-art learning-based methods.

scholarly journals Optimal Multi-View Surface Normal Estimation Using Affine Correspondences

2019 ◽  
Vol 28 (7) ◽  
pp. 3301-3311 ◽  
Author(s):  
Daniel Barath ◽  
Ivan Eichhardt ◽  
Levente Hajder
Keyword(s):  
Normal Estimation ◽  
Surface Normal

scholarly journals Eliminating the Effect of Reflectance Properties on Reconstruction in Stripe Structured Light System

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6564
Author(s):  
Zhao Song ◽  
Zhan Song ◽  
Yuping Ye
Keyword(s):  
Hybrid System ◽  
Surface Texture ◽  
Structured Light ◽  
Photometric Stereo ◽  
Free Form ◽  
Light Sources ◽  
Reconstruction Accuracy ◽  
Surface Geometry ◽  
Complex Objects ◽  
Structured Light System

The acquisition of the geometry of general scenes is related to the interplay of surface geometry, material properties and illumination characteristics. Surface texture and non-Lambertian reflectance properties degrade the reconstruction results by structured light technique. Existing structured light techniques focus on different coding strategy and light sources to improve reconstruction accuracy. The hybrid system consisting of a structured light technique and photometric stereo combines the depth value with normal information to refine the reconstruction results. In this paper, we propose a novel hybrid system consisting of stripe-based structured light and photometric stereo. The effect of surface texture and non-Lambertian reflection on stripe detection is first concluded. Contrary to existing fusion strategy, we propose an improved method for stripe detection to reduce the above factor’s effects on accuracy. The reconstruction problem for general scene comes down to using reflectance properties to improve the accuracy of stripe detection. Several objects, including checkerboard, metal-flat plane and free-form objects with complex reflectance properties, were reconstructed to validate our proposed method, which illustrates the effectiveness on improving the reconstruction accuracy of complex objects. The three-step phase-shifting algorithm was implemented and the reconstruction results were given and also compared with ours. In addition, our proposed framework provides a new feasible scheme for solving the ongoing problem of the reconstruction of complex objects with variant reflectance. The problem can be solved by subtracting the non-Lambertian components from the original grey values of stripe to improve the accuracy of stripe detection. In the future, based on stripe structured light technique, more general reflection models can be used to model different types of reflection properties of complex objects.

Design and Calibration of a 3D High-Resolution Surface Profiling System Using Photometric Stereo

2015 ◽  
Author(s):  
Boren Li ◽  
Tomonari Furukawa
Keyword(s):  
High Resolution ◽  
Light Intensity ◽  
Target Surface ◽  
Photometric Stereo ◽  
Radiometric Calibration ◽  
Geometric Calibration ◽  
Surface Profiling ◽  
Surface Normal ◽  
3D Methods ◽  
Intensity Calibration

This paper presents the design and calibration of a 3D high-resolution surface profiling system using photometric stereo (PS). This system is mainly composed of a high resolution DSLR camera with a macro lens facing perpendicularly to the target surface, and several LEDs tilting towards the surface constrained by a light fixture. With each LED turned on at a time to create one lighting direction, the camera fixed at the same position captures an image. PS with surface normal integration (SNI) are then performed to reconstruct the surface in 3D. Methods of four calibrations for the developed system are proposed to achieve better accuracy, which are the camera radiometric calibration, the camera geometric calibration, the light direction calibration and the light intensity calibration. Experiments have demonstrated that the developed system with the calibration processes could achieve the accuracy in the order of 10 microns.

scholarly journals Deep Photometric Stereo Networks for Determining Surface Normal and Reflectances

2020 ◽  
pp. 1-1
Author(s):  
Hiroaki Santo ◽  
Masaki Samejima ◽  
Yusuke Sugano ◽  
Boxin Shi ◽  
Yasuyuki Matsushita
Keyword(s):  
Photometric Stereo ◽  
Surface Normal
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