3D imaging spectroscopy for measuring hyperspectral patterns on solid objects

Kim, Min H.; Rushmeier, Holly; Dorsey, Julie; Harvey, Todd Alan; Prum, Richard O.; Kittle, David S.; Brady, David J.

doi:10.1145/2185520.2335389

Cited by 6 publications

(8 citation statements)

References 22 publications

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“…Spectral 3D acquisition systems: Existing systems for spectral 3D acquisition are roughly classified into photometric stereo-based [29,39], SfM and multi-view stereobased [21,49], and active lighting or scanner-based [19,27] systems. The photometric stereo-based systems [29,39] can acquire dense surface normals for every pixels of the single-view image.…”

Section: Related Workmentioning

confidence: 99%

“…However, they only can provide a sparse point cloud especially for a texture-less object. The active lighting or scanner-based systems [19,27] can provide an accurate and dense 3D model based on the active sensing. However, they require burdensome calibration of the entire system.…”

Section: Related Workmentioning

confidence: 99%

“…Some systems have also been proposed for spectral 3D acquisition [19,21,27,29,39,49]. However, they rely on a dedicated setup using a multispectral camera [27,39,49] or a multispectral light source [19,21,29], which makes the system impractical and expensive for most users.…”

Section: Introductionmentioning

confidence: 99%

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Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion

Monno

Hidaka

et al. 2019

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

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In this paper, we propose a novel projector-camera system for practical and low-cost acquisition of a dense object 3D model with the spectral reflectance property. In our system, we use a standard RGB camera and leverage an offthe-shelf projector as active illumination for both the 3D reconstruction and the spectral reflectance estimation. We first reconstruct the 3D points while estimating the poses of the camera and the projector, which are alternately moved around the object, by combining multi-view structured light and structure-from-motion (SfM) techniques. We then exploit the projector for multispectral imaging and estimate the spectral reflectance of each 3D point based on a novel spectral reflectance estimation model considering the geometric relationship between the reconstructed 3D points and the estimated projector positions. Experimental results on several real objects demonstrate that our system can precisely acquire a dense 3D model with the full spectral reflectance property using off-the-shelf devices.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion

Monno

Hidaka

et al. 2019

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

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“…In contrast to the material systems described before, these materials are typically crafted for direct application in order to fulfill a specific purpose, without further processing or assembly. The application areas of construction and building materials and material systems are widespread and range from cultural heritage applications (Li et al [LZS16]), civil engineering (Kim et al [KHK*12] and La et al [LGKN15]), private buildings and construction (Ham et al [HGF14]) to electronic devices (Protopopov et al [PD00]), printed circuit boards (PCBs) (Cicchiani et al [CHSW08]) or even micro‐electromechanical Systems (Fisher et al [FH08]).…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

“…They also apply color coded isolines as an overlay to visualize uncertainty inside the specimen. Labeling in hyperspectral imagery to distinguish between different materials in 3D is presented by Kim et al [KHK*12]. Hyperspectral imaging is used for inspecting artifacts from geology and cultural heritage.…”

Section: Visual Computing In Materials Sciencementioning

confidence: 99%

STAR: Visual Computing in Materials Science

Heinzl

Stappen

2017

Computer Graphics Forum

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Visual computing has become highly attractive for boosting research endeavors in the materials science domain. Using visual computing, a multitude of different phenomena may now be studied, at various scales, dimensions, or using different modalities. This was simply impossible before. Visual computing techniques provide novel insights in order to understand complex material systems of interest, which is demonstrated by strongly rising number of new approaches, publishing new techniques for materials analysis and simulation. Outlining the proximity of materials science and visual computing, this state of the art report focuses on the intersection of both domains in order to guide research endeavors in this field. We provide a systematic survey on the close interrelations of both fields as well as how they profit from each other. Analyzing the existing body of literature, we review the domain of visual computing supported materials science, starting with the definition of materials science as well as material systems for which visual computing is frequently used. Major tasks for visual computing, visual analysis and visualization in materials sciences are identified, as well as simulation and testing techniques, which are providing the data for the respective analyses. We reviewed the input data characteristics and the direct and derived outputs, the visualization techniques and visual metaphors used, as well as the interactions and analysis workflows employed. All our findings are finally integrated in a cumulative matrix, giving insights about the different interrelations of both domains. We conclude our report with the identification of open high level and low level challenges for future research.

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High‐fidelity iridal light transport simulations at interactive rates

Kravchenko

Baranoski

Chen

et al. 2017

Computer Animation & Virtual

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Predictive light transport models based on first-principles simulation approaches have been proposed for complex organic materials. The driving force behind these efforts has been the high-fidelity reproduction of material appearance attributes without one having to rely on the manipulation of ad hoc parameters. These models, however, are usually considered excessively time consuming for rendering and visualization applications requiring interactive rates. In this paper, we propose a strategy to address this open problem with respect to one of the most challenging of these organic materials, namely the human iris. More specifically, starting with the configuration of a predictive iridal light transport model on a parallel-computing platform, we analyze the sensitivity of iridal appearance attributes to key model running parameters in order to achieve an optimal balance between fidelity and performance. We believe that the proposed strategy represents a step toward the real-time and predictive synthesis of high-fidelity iridal images for rendering and visualization applications, and it can be extended to other organic materials.

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3D imaging spectroscopy for measuring hyperspectral patterns on solid objects

Cited by 6 publications

References 22 publications

Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion

Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion

STAR: Visual Computing in Materials Science

High‐fidelity iridal light transport simulations at interactive rates

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