“…Some researchers (Morris and Kutulakos, 2011;Ding et al, 2011) employed stereo/multiple cameras to record the refractive surface, relying on a cross-view normal consistency constraint: the normals computed using the pixel-point correspondences obtained from multiple viewpoints must be consistent. Alternatively, some studies have been conducted (Ye et al, 2012;Wetzstein et al, 2011;Tsai, 2020;Tsai et al, 2021) to estimate ray-ray correspondences utilizing specific devices such as Bokode (Ye et al, 2012) and light field probes (Wetzstein et al, 2011;Tsai et al, 2021) by capturing the incident rays released from the background and the exiting rays traveling to the camera. Although 3D results appear to be highly promising, the high cost of such devices is an important downside of these approaches.…”
Section: Direct Ray Measurementmentioning
confidence: 99%
“…In addition, one of the main common shortcomings of the aforementioned approaches is that they provide only dependable normals but noisy depths. To provide the boundary condition for the integration of normal, they need to presume a planer surface near the boundary (Ye et al, 2012;Ding et al, 2011) or approximate the border using noisy depths (Morris and Kutulakos, 2011;Wetzstein et al, 2011). To address the restrictions mentioned above, Qian et al (2016Qian et al ( , 2017 propose a position-normal consistency based on a global optimization method to restore depth maps of the surface from front and back.…”
Abstract. In the field of industrial metrology, there is a rising need for 3D information at a very high resolution for micro-measurements and quality control of transparent objects such as glass bottles (beer, wine, cola, cosmetics, etc.). However, such objects are particularly challenging for optical-based 3D reconstruction methods and systems such as photogrammetry, photometric stereo, structured light scanning, laser scanning, typically resulting in poor metrological performances. Indeed, these methods require the surface of the object to diffusely reflect the incoming light, which is not the case with the glass material where refraction and absorption phenomena do not permit their use. Over the years, various methods have been investigated and developed to avoid the coating (or powdering) treatment often used to make transparent objects opaque and diffusely reflecting. Most of the approaches require either some a priori knowledge of the transparent object or assumptions about how light interacts with the surface. This paper provides a general overview of state-of-the-art 3D digitization methods for optically non-cooperative surfaces featuring absorption, scattering, and refraction. The paper reviews research works summarizing them into four categories including shape-from-X, direct ray measurements, hybrid, and learning-based approaches. Moreover, we provided some 3D results to better highlight the advantages and disadvantages of each method in practice when dealing with transparent objects.
“…Some researchers (Morris and Kutulakos, 2011;Ding et al, 2011) employed stereo/multiple cameras to record the refractive surface, relying on a cross-view normal consistency constraint: the normals computed using the pixel-point correspondences obtained from multiple viewpoints must be consistent. Alternatively, some studies have been conducted (Ye et al, 2012;Wetzstein et al, 2011;Tsai, 2020;Tsai et al, 2021) to estimate ray-ray correspondences utilizing specific devices such as Bokode (Ye et al, 2012) and light field probes (Wetzstein et al, 2011;Tsai et al, 2021) by capturing the incident rays released from the background and the exiting rays traveling to the camera. Although 3D results appear to be highly promising, the high cost of such devices is an important downside of these approaches.…”
Section: Direct Ray Measurementmentioning
confidence: 99%
“…In addition, one of the main common shortcomings of the aforementioned approaches is that they provide only dependable normals but noisy depths. To provide the boundary condition for the integration of normal, they need to presume a planer surface near the boundary (Ye et al, 2012;Ding et al, 2011) or approximate the border using noisy depths (Morris and Kutulakos, 2011;Wetzstein et al, 2011). To address the restrictions mentioned above, Qian et al (2016Qian et al ( , 2017 propose a position-normal consistency based on a global optimization method to restore depth maps of the surface from front and back.…”
Abstract. In the field of industrial metrology, there is a rising need for 3D information at a very high resolution for micro-measurements and quality control of transparent objects such as glass bottles (beer, wine, cola, cosmetics, etc.). However, such objects are particularly challenging for optical-based 3D reconstruction methods and systems such as photogrammetry, photometric stereo, structured light scanning, laser scanning, typically resulting in poor metrological performances. Indeed, these methods require the surface of the object to diffusely reflect the incoming light, which is not the case with the glass material where refraction and absorption phenomena do not permit their use. Over the years, various methods have been investigated and developed to avoid the coating (or powdering) treatment often used to make transparent objects opaque and diffusely reflecting. Most of the approaches require either some a priori knowledge of the transparent object or assumptions about how light interacts with the surface. This paper provides a general overview of state-of-the-art 3D digitization methods for optically non-cooperative surfaces featuring absorption, scattering, and refraction. The paper reviews research works summarizing them into four categories including shape-from-X, direct ray measurements, hybrid, and learning-based approaches. Moreover, we provided some 3D results to better highlight the advantages and disadvantages of each method in practice when dealing with transparent objects.
“…The surface can also be used as a mirror in order to compare an original and mirrored image in what is known as pattern fringe reflectometry [20,21]. Alternatively, the distortion of a pattern behind the liquid can be employed [22,23], an approach that has been addressed with deep neural networks in modern works [24]. Particle image velocimetry makes use of the motion of seeding particles in the fluid [25,26].…”
“…Among them, displacement sensors [11,[18][19][20][21], dynamometers [22], lateral cameras [7,9,[23][24][25][26][27] or ultrasonic Doppler shift devices [19,28,29]. In the last decades, the increase in compu- * alvaro.romerocalvo@colorado.edu ORCID(s): 0000-0003-3369-8460 (Á. Romero-Calvo) tational power has motivated the application of optical methods, such as stereo imaging [30], digital image correlation [31][32][33][34][35], pattern fringe reflectometry [36,37], or particle image velocimetry [38,39]. Alternative approaches employ the movement of a float [40], or the distortion of a laser on the surface [41] to obtain liquid level measurements.…”
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