3-D Computer Vision Using Structured Light: Design, Calibration, and Implementation Issues

DePiero, Fred W.; Trivedi, Mohan M.

doi:10.1016/s0065-2458(08)60646-4

Cited by 77 publications

(34 citation statements)

References 56 publications

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“…Some techniques use a rig and carefully calibrated adjustablerange targets. This provides known ranges that can be used to solve for a set of model parameters related to the projectivity [14]. It is also possible to use direct measurements of the endpoints of target contours illuminated by the laser during the calibration procedure [22].…”

Section: A Calibrationmentioning

confidence: 99%

“…Another class of three dimensional laser mapping systems use the triangulation relationship between a structured light pattern and camera sensor to solve for the scene geometry. This type of laser stripe imaging has been a common technique for many land applications in robotics and industrial measurement systems [14]. It has also been used on some underwater vehicles [15], [16] but only a few examples have been given thus far and a general approach has not been presented.…”

Section: Introductionmentioning

confidence: 99%

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Application of structured light imaging for high resolution mapping of underwater archaeological sites

Roman

Inglis

Rutter

2010

Oceans'10 Ieee Sydney

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Abstract-This paper presents results from recent work using structured light laser profile imaging to create high resolution bathymetric maps of underwater archaeological sites. Documenting the texture and structure of submerged sites is a difficult task and many applicable acoustic and photographic mapping techniques have recently emerged. This effort was completed to evaluate laser profile imaging in comparison to stereo imaging and high frequency multibeam mapping. A ROV mounted camera and inclined 532 nm sheet laser were used to create profiles of the bottom that were then merged into maps using platform navigation data. These initial results show very promising resolution in comparison to multibeam and stereo reconstructions, particularly in low contrast scenes. At the test sites shown here there were no significant complications related to scattering or attenuation of the laser sheet by the water. The resulting terrain was gridded at 0.25 cm and shows overall centimeter level definition. The largest source of error was related to the calibration of the laser and camera geometry. Results from three small areas show the highest resolution 3D models of a submerged archaeological site to date and demonstrate that laser imaging will be a viable method for accurate three dimensional site mapping and documentation.

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Section: A Calibrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of structured light imaging for high resolution mapping of underwater archaeological sites

Roman

Inglis

Rutter

2010

Oceans'10 Ieee Sydney

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“…The PRIME 3D scanning system [1] uses one camera, one laser line projector, and a controlled conveyor belt to image different types of objects as seen in Figure 1. The encoder wheel provides displacement information of the object, and as the object passes through the light stripe, the camera acquires many images that are later aligned using the displacement information.…”

Section: Acquisitionmentioning

confidence: 99%

“…Traditionally, most methods similar to PRIME [1] find the center of the light stripe to subpixel accuracy in the spatial domain by assuming a Gaussian profile for the stripe cross-section. However, others have proposed using time domain analysis to find depth points for an image.…”

Section: Data Processingmentioning

confidence: 99%

Three-Dimensional Facial Imaging Using a Static Light Screen (SLS) and a Dynamic Subject

McKeon

Flynn

2010

IEEE Trans. Instrum. Meas.

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“…The 'Sensor' images appearing herein were acquired using a structured light range sensor, similar to [3]. The sensor used a laser line generator that casts a plane of light from a diode source.…”

Section: Testingmentioning

confidence: 99%

Fast landmark-based registration via deterministic and efficient processing, some preliminary results

DePiero

Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission

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AbstractΩ Project sponsored, in part, by the Department of the Navy, Office of Naval Research. Approach Based on Subgraph MatchingThe goal of this research is to pursue a technique that can perform view registration at rates approaching 10 Hz, without any user input for initial estimates. This performance goal is set to match the data rates of range cameras. It is also desired to have a method that computes the rigid transformation (translation plus rotation) in the presence of possible scale changes. Registration at these rates could permit sensor motion to be tracked in realtime. This would permit unconstrained movement of a sensor across a large scene.To achieve fast and deterministic processing, iterative, or random [6] approaches were avoided. Established methods do not typically separate the steps of determining corresponding points and determining the transform. This limits compute speed. In the new approach these steps have been kept separate, and are implemented in a non-iterative fashion. This is an important difference for the new approach. Another difference is that correspondence between the data sets is determined only for select feature points. This improves processing speed, but it does limit accuracy.Correspondence between the data sets is determined via graph matching. Graphs are formed using salient features in each range image. Graph matching is accomplished using the LeRP Algorithm [2] [4]. LeRP approximates a subgraph isomorphism via a deterministic procedure, based on the comparison of length-r paths. The LeRP algorithm yields a set of corresponding locations in the two input range images, from which the absolute orientation may be found via closed-form solution [9].A typical graph appears in Figure 1. The white segments designate an accurately matched subgraph for the scene. Approach -Salient FeaturesGraphs describe the salient features in each range image. For rapid detection, local, well isolated, peaks in the range data were used to form the image features. These are desirable because they are likely to remain in view with small shifts in scene.The significant percentage of black segments shown in Figure 1 demonstrates a lack of stability in feature detection. Stable and invariant feature detection -via fast, efficient, deterministic means -remains the greatest challenge in this new approach. While the lack of stability shown in the figure is undesirable, it was deemed an appropriate tradeoff in terms of processing speed. Other techniques employ more robust local features [10] but require more processing time. The approach taken here was to rely on the LeRP matching algorithm to determine appropriate correspondences, despite noisy features.Some reported techniques use invariant features that involve curvature, moments, or spherical harmonics [18]. These types of features react to jump discontinuities that may occur at a limb [19]. Such feature points were avoided in this new approach. Consider the occurrence of a limb where the line-of-sight of a sensor becomes tangent to a hillside. ...

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3-D Computer Vision Using Structured Light: Design, Calibration, and Implementation Issues

Cited by 77 publications

References 56 publications

Application of structured light imaging for high resolution mapping of underwater archaeological sites

Application of structured light imaging for high resolution mapping of underwater archaeological sites

Three-Dimensional Facial Imaging Using a Static Light Screen (SLS) and a Dynamic Subject

Fast landmark-based registration via deterministic and efficient processing, some preliminary results

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