Investigating 3d Reconstruction of Non-Collaborative Surfaces Through Photogrammetry and Photometric Stereo

Karami, Ali; Menna, Fabio; Remondino, Fabio

doi:10.5194/isprs-archives-xliii-b2-2021-519-2021

Cited by 13 publications

(24 citation statements)

References 47 publications

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“…Since there is no studies on utilizing photometric stereo approach to reconstruct 3D models of carpological materials or any plant parts, the uncertainty of photometric stereo still exists. Meanwhile, improper assumptions could also lead to global deformation and shape inaccuracy of the 3D models [ 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery

et al. 2022

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This study provides an accurate and efficient method to reconstruct detailed and high-resolution digital 3D models of carpological materials by photogrammetric method, in which only about 100 to 150 images are required for each model reconstruction. The 3D models reflect the realistic morphology and genuine color of the carpological materials. The 3D models are scaled to represent the true size of the materials even as small as 3 mm in diameter. The interfaces are interactive, in which the 3D models can be rotated in 360° to observe the structures and be zoomed to inspect the macroscopic details. This new platform is beneficial for developing a virtual herbarium of carpological collection which is thus the most important to botanical authentication and education.

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Section: Discussionmentioning

confidence: 99%

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery

et al. 2022

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“…Photogrammetry has also been used in hybrid systems (Lim et al., 2005; Wu et al., 2009; Park et al., 2013, 2016; Grochulla and Thormählen, 2015; Logothetis et al., 2019; Li et al., 2020; Xie, 2020; Karami et al., 2021). MVS approaches are used to create a sparse 3D shape of an object, free from global deformation, used as a base for high‐resolution measurements produced using the PS concept.…”

Section: Related Workmentioning

confidence: 99%

“…With respect to Karami et al. (2021), who presented the overall system architecture and some initial results, the present article focuses on the concept of utilising light directionality to increase texture quality by exploiting shade and shadow phenomena in detail with various critical analyses.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Light Directionality for Image‐Based 3D Reconstruction of Non‐Collaborative Surfaces

Karami

Menna

Remondino

et al. 2022

The Photogrammetric Record

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Three-dimensional (3D) measurement of non-collaborative surfaces is still an open research topic. This paper investigates and quantifies for the first time the effect of light directionality and fusion of multiple images as a method to improve the quality of photogrammetric 3D reconstruction. For this aim, an image acquisition system that employs multiple light sources was developed to highlight the roughness and microstructures of the object under investigation. Images were captured at various grazing angles to highlight the local surface roughness and microstructures. Individual point clouds, created using images taken at different grazing angles, were produced using dense image-matching techniques. These point clouds were then compared against different 3D photogrammetric reconstructions obtained from a pre-processing of the acquired images based on diffuse lighting, median and average images. Experiments showed that exploiting light directionality significantly improves image-matching quality. Furthermore, depending on the light direction, the root mean square (RMS) error of the 3D surfaces obtained using the proposed system were up to 50% less than those created by traditional diffuse lighting.

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“…However, it is still challenging to achieve high-accuracy 3D measurement of non-collaborative objects ( Figure 1 ) due to the sensitivity of photogrammetry to the textural properties of the surface [ 22 , 23 , 24 ]. For example, when the surface of an object is featureless or displays repetitive patterns, all methods based on feature extraction face difficulties in finding a sufficient number of corresponding image points that are needed for image orientation [ 1 , 25 ]. In case of polished and shiny surfaces, such as industrial and metallic components ( Figure 1 ), the incoming light is subject to the law of reflection and is observed as specular reflection.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, we co-register and fuse all obtained 3D measurements to generate a precise and complete 3D reconstruction of non-collaborative objects. The paper builds upon [ 11 , 25 ], in which they only present the main concept and high-level architecture of the prototype system developed in the FBK-3DOM laboratory to synergistically combine photogrammetry and photometric stereo methods. They discuss one of its main components, for instance, the concept of utilizing light directionality to increase texture quality by exploiting shade and shadow phenomena in detail and only addressed parallel light direction without taking intensity attenuation into account.…”

Section: Introductionmentioning

confidence: 99%

Combining Photogrammetry and Photometric Stereo to Achieve Precise and Complete 3D Reconstruction

Karami

Menna²,

Remondino³

2022

Sensors

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Image-based 3D reconstruction has been employed in industrial metrology for micro-measurements and quality control purposes. However, generating a highly-detailed and reliable 3D reconstruction of non-collaborative surfaces is still an open issue. In this paper, a method for generating an accurate 3D reconstruction of non-collaborative surfaces through a combination of photogrammetry and photometric stereo is presented. On one side, the geometric information derived with photogrammetry is used in areas where its 3D measurements are reliable. On the other hand, the high spatial resolution capability of photometric stereo is exploited to acquire a finely detailed topography of the surface. Finally, three different approaches are proposed to fuse both geometric information and high frequency details. The proposed method is tested on six different non-collaborative objects with different surface characteristics. To evaluate the accuracy of the proposed method, a comprehensive cloud-to-cloud comparison between reference data and 3D points derived from the proposed fusion methods is provided. The experiments demonstrated that, despite correcting global deformation up to an average RMSE of less than 0.1 mm, the proposed method recovers the surface topography at the same high resolution as the photometric stereo.

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Investigating 3d Reconstruction of Non-Collaborative Surfaces Through Photogrammetry and Photometric Stereo

Cited by 13 publications

References 47 publications

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery

Photogrammetric reconstruction of 3D carpological collection in high resolution for plants authentication and species discovery

Exploiting Light Directionality for Image‐Based 3D Reconstruction of Non‐Collaborative Surfaces

Combining Photogrammetry and Photometric Stereo to Achieve Precise and Complete 3D Reconstruction

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