Evaluation of synthetically generated patterns for image-based 3D reconstruction of texture-less objects

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

“…On the contrary, photogrammetry still performs poorly on objects with shiny or textureless surfaces. To resolve the problem, the authors proposed to project a known (Hafeez et al, 2017(Hafeez et al, , 2020Menna et al, 2017), random (Hosseininaveh et al, 2015;Ahmadabadian et al, 2017Ahmadabadian et al, , 2019 or synthetic (Hafeez et al, 2018(Hafeez et al, , 2020Santo si et al, 2019) pattern onto the object. Menna et al (2016) created an automated workflow based on pattern projection for 3D digitisation of heritage artifacts: various known random patterns are used to enhance dense image-matching.…”

“…On the contrary, photogrammetry still performs poorly on objects with shiny or textureless surfaces. To resolve the problem, the authors proposed to project a known (Hafeez et al., 2017, 2020; Menna et al., 2017), random (Hosseininaveh et al., 2015; Ahmadabadian et al., 2017, 2019) or synthetic (Hafeez et al., 2018, 2020; Santoši et al., 2019) pattern onto the object. Menna et al.…”

“…The performance of such techniques degrades on real-world objects with properties such as interreflection and specular reflection (Abzal et al, 2018), which frequently exhibit non-Lambertian reflectance (Goldman et al, 2009;Shi et al, 2013Shi et al, , 2018Park et al, 2016;Li et al, 2020). As a result, instead of assuming the Lambertian reflectance model, some methods use a more complex and/or physical light model when interacting with the surface (Alldrin et al, 2008;Xie et al, 2010;Lu et al, 2013;Zheng et al, 2019;Boss et al, 2020;Santo et al, 2020). Nevertheless, although most PS-based algorithms can recover high-frequency details of a non-collaborative surface, lowfrequency global shape deformation often remains in the resulting model (MacDonald, 2015;Park et al, 2016;Fan et al, 2017;Shi et al, 2018;Li et al, 2020;Ren et al, 2021).…”

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

“…Over the years, different photogrammetric methods have been developed to deal with the 3D reconstruction of noncollaborative objects. For 3D reconstruction of Lambertian textureless objects, previous studies have been concentrated on improving surface texture by projecting, for example, a known pattern (Menna et al, 2017;Mousavi et al, 2018), random (Hosseininaveh et al, 2015;Ahmadabadian et al, 2019) or a synthetic texture (Santoši et al, 2019;Hafeez et al, 2020) onto the objects. These methods, however, assume that the object surface is Lambertian, which is not the case with objects that have specular reflection or interreflection effects.…”

“…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 (e.g., opaque, translucent, roughness). Consequently, noisy results on poorly textured objects are typically generated (Ahmadabadian et al, 2017;Santoši et al, 2019;Hafeez et al, 2020). Unlike photogrammetry approaches, photometric stereo can recover a very detailed topography of objects even with textureless or shiny surfaces (Li et al, 2020;Wang et al, 2020;Wei et al, 2020).…”