349 research outputs found
Linear Differential Constraints for Photo-polarimetric Height Estimation
In this paper we present a differential approach to photo-polarimetric shape
estimation. We propose several alternative differential constraints based on
polarisation and photometric shading information and show how to express them
in a unified partial differential system. Our method uses the image ratios
technique to combine shading and polarisation information in order to directly
reconstruct surface height, without first computing surface normal vectors.
Moreover, we are able to remove the non-linearities so that the problem reduces
to solving a linear differential problem. We also introduce a new method for
estimating a polarisation image from multichannel data and, finally, we show it
is possible to estimate the illumination directions in a two source setup,
extending the method into an uncalibrated scenario. From a numerical point of
view, we use a least-squares formulation of the discrete version of the
problem. To the best of our knowledge, this is the first work to consider a
unified differential approach to solve photo-polarimetric shape estimation
directly for height. Numerical results on synthetic and real-world data confirm
the effectiveness of our proposed method.Comment: To appear at International Conference on Computer Vision (ICCV),
Venice, Italy, October 22-29, 201
Polarisation photometric stereo
© 2017 This paper concerns a novel approach to fuse two-source photometric stereo (PS) data with polarisation information for complete surface normal recovery for smooth or slightly rough surfaces. PS is a well-established method but is limited in application by its need for three or more well-spaced and known illumination sources and Lambertian reflectance. Polarisation methods are less studied but have shown promise for smooth surfaces under highly controlled capture conditions. However, such methods suffer from inherent ambiguities and the depolarising effects of surface roughness. The method presented in this paper goes some way to overcome these limitations by fusing the most reliable information from PS and polarisation. PS is used with only two sources to deduce a constrained mapping of the surface normal at each point onto a 2D plane. Phase information from polarisation is used to deduce a mapping onto a different plane. The paper then shows how the full surface normal can be obtained from the two mappings. The method is tested on a range of real-world images to demonstrate the advantages over standalone applications of PS or polarisation methods
High Resolution Surface Reconstruction of Cultural Heritage Objects Using Shape from Polarization Method
Nowadays, three-dimensional reconstruction is used in various fields like computer vision, computer graphics, mixed reality and digital twin. The three- dimensional reconstruction of cultural heritage objects is one of the most important applications in this area which is usually accomplished by close range photogrammetry. The problem here is that the images are often noisy, and the dense image matching method has significant limitations to reconstruct the geometric details of cultural heritage objects in practice. Therefore, displaying high-level details in three-dimensional models, especially for cultural heritage objects, is a severe challenge in this field. In this paper, the shape from polarization method has been investigated, a passive method with no drawbacks of active methods. In this method, the resolution of the depth maps can be dramatically increased using the information obtained from the polarization light by rotating a linear polarizing filter in front of a digital camera. Through these polarized images, the surface details of the object can be reconstructed locally with high accuracy. The fusion of polarization and photogrammetric methods is an appropriate solution for achieving high resolution three-dimensional reconstruction. The surface reconstruction assessments have been performed visually and quantitatively. The evaluations showed that the proposed method could significantly reconstruct the surfaces' details in the three-dimensional model compared to the photogrammetric method with 10 times higher depth resolution
Polarimetric Multi-View Inverse Rendering
A polarization camera has great potential for 3D reconstruction since the
angle of polarization (AoP) and the degree of polarization (DoP) of reflected
light are related to an object's surface normal. In this paper, we propose a
novel 3D reconstruction method called Polarimetric Multi-View Inverse Rendering
(Polarimetric MVIR) that effectively exploits geometric, photometric, and
polarimetric cues extracted from input multi-view color-polarization images. We
first estimate camera poses and an initial 3D model by geometric reconstruction
with a standard structure-from-motion and multi-view stereo pipeline. We then
refine the initial model by optimizing photometric rendering errors and
polarimetric errors using multi-view RGB, AoP, and DoP images, where we propose
a novel polarimetric cost function that enables an effective constraint on the
estimated surface normal of each vertex, while considering four possible
ambiguous azimuth angles revealed from the AoP measurement. The weight for the
polarimetric cost is effectively determined based on the DoP measurement, which
is regarded as the reliability of polarimetric information. Experimental
results using both synthetic and real data demonstrate that our Polarimetric
MVIR can reconstruct a detailed 3D shape without assuming a specific surface
material and lighting condition.Comment: Paper accepted in IEEE Transactions on Pattern Analysis and Machine
Intelligence (2022). arXiv admin note: substantial text overlap with
arXiv:2007.0883
In-process surface profile assessment of rotary machined timber using a dynamic photometric stereo technique
Machining operations have advanced in speed and there is an increasing demand for higher quality surface finish. It is
therefore necessary to develop real-time surface inspection techniques which will provide sensory information for controlling
the machining processes. This paper describes a practical method for real-time analysis of planed wood using the
photometric stereo technique. Earlier research has shown that the technique is very effective in assessing surface waviness
on static wood samples. In this paper, the photometric stereo method is extended to real industrial applications
where samples are subjected to rapid movements. Surface profiles extracted from the dynamic photometric stereo
method are compared with those from the static measurements and the results show that there is a high correlation
between the two methods
Linear Depth Estimation from an Uncalibrated, Monocular Polarisation Image
We present a method for estimating surface height directly from a single polarisation image simply by solving a large, sparse system of linear equations. To do so, we show how to express polarisation constraints as equations that are linear in the unknown depth. The ambiguity in the surface normal azimuth angle is resolved globally when the optimal surface height is reconstructed. Our method is applicable to objects with uniform albedo exhibiting diffuse and specular reflectance. We extend it to an uncalibrated scenario by demonstrating that the illumination (point source or first/second order spherical harmonics) can be estimated from the polarisation image, up to a binary convex/concave ambiguity. We believe that our method is the first monocular, passive shape-from-x technique that enables well-posed depth estimation with only a single, uncalibrated illumination condition. We present results on glossy objects, including in uncontrolled, outdoor illumination
Polarimetric Multi-View Inverse Rendering
A polarization camera has great potential for 3D reconstruction since the
angle of polarization (AoP) of reflected light is related to an object's
surface normal. In this paper, we propose a novel 3D reconstruction method
called Polarimetric Multi-View Inverse Rendering (Polarimetric MVIR) that
effectively exploits geometric, photometric, and polarimetric cues extracted
from input multi-view color polarization images. We first estimate camera poses
and an initial 3D model by geometric reconstruction with a standard
structure-from-motion and multi-view stereo pipeline. We then refine the
initial model by optimizing photometric and polarimetric rendering errors using
multi-view RGB and AoP images, where we propose a novel polarimetric rendering
cost function that enables us to effectively constrain each estimated surface
vertex's normal while considering four possible ambiguous azimuth angles
revealed from the AoP measurement. Experimental results using both synthetic
and real data demonstrate that our Polarimetric MVIR can reconstruct a detailed
3D shape without assuming a specific polarized reflection depending on the
material.Comment: Paper accepted in ECCV 202
Polarized 3D: High-Quality Depth Sensing with Polarization Cues
Coarse depth maps can be enhanced by using the shape information from polarization cues. We propose a framework to combine surface normals from polarization (hereafter polarization normals) with an aligned depth map. Polarization normals have not been used for depth enhancement before. This is because polarization normals suffer from physics-based artifacts, such as azimuthal ambiguity, refractive distortion and fronto-parallel signal degradation. We propose a framework to overcome these key challenges, allowing the benefits of polarization to be used to enhance depth maps. Our results demonstrate improvement with respect to state-of-the-art 3D reconstruction techniques.Charles Stark Draper Laboratory (Doctoral Fellowship)Singapore. Ministry of Education (Academic Research Foundation MOE2013-T2-1-159)Singapore. National Research Foundation (Singapore University of Technology and Design
Linear Differential Constraints for Photo-polarimetric Height Estimation
In this paper we present a differential approach to photopolarimetric shape estimation. We propose several alternative differential constraints based on polarisation and photometric shading information and show how to express them in a unified partial differential system. Our method uses the image ratios technique to combine shading and polarisation information in order to directly reconstruct surface height, without first computing surface normal vectors. Moreover, we are able to remove the non-linearities so that the problem reduces to solving a linear differential problem. We also introduce a new method for estimating a polarisation image from multichannel data and, finally, we show it is possible to estimate the illumination directions in a two source setup, extending the method into an uncalibrated scenario. From a numerical point of view, we use a least-squares formulation of the discrete version of the problem. To the best of our knowledge, this is the first work to consider a unified differential approach to solve photo-polarimetric shape estimation directly for height. Numerical results on synthetic and real-world data confirm the effectiveness of our proposed method
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