On 3D Model Construction by Fusing Heterogeneous Sensor Data

Yuesong, Wang,; Wang, Jih-Fang

doi:10.1006/ciun.1994.1048

Cited by 14 publications

(3 citation statements)

References 31 publications

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“…These datasets overlap because agents bring data that become available later as a consistent update. This synthesis of datasets that were created at various times and which may overlap [47] is similar to restoring data from incremental backups and to the fusion of asynchronous sensor data [48]. Meaningful summaries can be done up to the date of the update that completes the data pool, even if a part of the data is received in near-real-time.…”

Section: Datasets and Data Valuesmentioning

confidence: 99%

Anatomy of data integration

Brazhnik

Jones

2007

Journal of Biomedical Informatics

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Producing reliable information is the ultimate goal of data processing. The ocean of data created with the advances of science and technologies calls for integration of data coming from heterogeneous sources that are diverse in their purposes, business rules, underlying models and enabling technologies. Reference models, Semantic Web, standards, ontology, and other technologies enable fast and efficient merging of heterogeneous data, while the reliability of produced information is largely defined by how well the data represent the reality. In this paper, we initiate a framework for assessing the informational value of data that includes data dimensions; aligning data quality with business practices; identifying authoritative sources and integration keys; merging models; uniting updates of varying frequency and overlapping or gapped data sets.

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Section: Datasets and Data Valuesmentioning

confidence: 99%

Anatomy of data integration

Brazhnik

Jones

2007

Journal of Biomedical Informatics

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“…The most relevant work has focused on real-time spline surface reconstruction of an object by modifying a spline surface with Kalman filtered range scan measurements. [12][13][14] This work lays the foundation for using DVL measurements to create a real-time spline-based terrain reconstruction that enables the generation of a smooth camera orientation command.…”

Section: Introductionmentioning

confidence: 99%

Navigation for Performing Visual Surveys of Non-Planar Surfaces

Murthy

Rock

2009

AIAA Guidance, Navigation, and Control Conference

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This paper addresses the problem of navigating a robotic vehicle over non-planar surfaces for the purpose of performing visual surveys. The key issue lies in generating a spatiallysmooth camera orientation command that will point the camera toward the surface during surface traversal. The proposed solution filters high spatial frequency local surface measurements using a low spatial frequency spline-based model of the surface. The filtering occurs by updating the spline surface model with local measurements using a linear Kalman filter. Subsequently, the spline point projection algorithm generates the camera orientation command from the updated spline surface. The results show that when the spline-based surface model is used to smooth the high frequency measurements, the resulting camera orientation command resembles a spatially-smoothed version of the orientation command produced by local surface orientation measurements. Though the results of this paper focus on underwater visual survey applications, the proposed solution could be applied to any visual survey of a high spatial frequency surface, such as spacecraft inspection.

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“…of the designed environment. One exciting avenue to explore here is incorporating work in computer-vision and range sensing, and recent work by Wang and Wang [19] and Lavallée and Szeliski [10] use B-spline surfaces as the basis of visual reconstruction experiments, which strengthens our use of B-splines as a mathematical basis for the system. Moving on from this we intend to develop a system whereby robots can be programmed in a wholly graphical environment, rather than graphical systems being used to test text-based programs [2].…”

Section: Development Of a Systemmentioning

confidence: 97%