Expert system-based design of close-range photogrammetric networks

Mason, Scott

doi:10.1016/0924-2716(95)90117-w

Cited by 34 publications

(41 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The basic quantitative aids to design are covariance estimation in a suitably chosen gauge (see §9) and the quality control tests from §10. Expert systems have been developed [79], but in practice most designs are still based on personal experience and rules of thumb.…”

Section: Network Designmentioning

confidence: 99%

See 1 more Smart Citation

Bundle Adjustment — A Modern Synthesis

Triggs

McLauchlan

Hartley

et al. 2000

Lecture Notes in Computer Science

3,003

2,203

View full text Add to dashboard Cite

This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics covered include: the choice of cost function and robustness; numerical optimization including sparse Newton methods, linearly convergent approximations, updating and recursive methods; gauge (datum) invariance; and quality control. The theory is developed for general robust cost functions rather than restricting attention to traditional nonlinear least squares.

show abstract

Section: Network Designmentioning

confidence: 99%

“…We will not say much about design, merely outlining the basic considerations and giving a few useful rules of thumb. See [5, chapter 6], [79,78], [73, Vol.2 §4] for more information.…”

Section: Network Designmentioning

confidence: 99%

Bundle Adjustment — A Modern Synthesis

Triggs

McLauchlan

Hartley

et al. 2000

Lecture Notes in Computer Science

3,003

2,203

View full text Add to dashboard Cite

show abstract

“…Network design, or camera configuration, for a photogrammetry-based method significantly affects the accuracy. An order of magnitude of improvement is achieved with four highly convergent cameras over the case of two nearly parallel cameras 26,27 . Achieving an optimum configuration in an indoor environment where the objective is to model every surface in that environment may be unrealizable or at least impractical.…”

Section: Choosing the Optimum Approachmentioning

confidence: 90%

<title>Experimental analysis and design considerations of virtual environments creation</title>

1998

View full text Add to dashboard Cite

Selecting the appropriate 3-D capture and modeling technologies to create the contents of a virtual environment (VE) remains a challenging task. One of the objectives of the environment-modeling project in our laboratory is to develop a design strategy for selecting the optimum sensor technology and its configuration to meet the requirements for virtual environment applications. This will be based on experimental evaluation of all performance aspects of several systems for creating virtual environments. The main problems include: practical sensor calibration, the registration of images particularly in large sites in the absence of GPS and control points, the complete and accurate coverage of all details, and maintaining realistic-look at real-time rate. This paper focuses on the evaluation of the performance of some approaches to virtual environment creation using specifically designed laboratory experimentation. By understanding the potentials and limitations of each method, we are able to select the optimum one for a given application.

show abstract

“…Designing the imaging network (Fraser, 1996;Mason, 1995) is still a challenging task in photogrammetry due to many factors related to the nature and complexity of the study object, the used camera, accessibility and visibility. In Alsadik et al (2013) an approach for optimal network design for cultural heritage objects (like buildings and statues) is presented.…”

Section: Camera Network Design and Image Capturementioning

confidence: 99%

Robust extraction of image correspondences exploiting the image scene geometry and approximate camera orientation

Alsadik

Remondino

Menna

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:Image-based modeling techniques are an important tool for producing 3D models in a practical and cost effective manner. Accurate image-based models can be created as long as one can retrieve precise image calibration and orientation information which is nowadays performed automatically in computer vision and photogrammetry. The first step for orientation is to have sufficient correspondences across the captured images. Keypoint descriptors like SIFT or SURF are a successful approach for finding these correspondences. The extraction of precise image correspondences is crucial for the subsequent image orientation and image matching steps. Indeed there are still many challenges especially with wide-baseline image configuration. After the extraction of a sufficient and reliable set of image correspondences, a bundle adjustment is used to retrieve the image orientation parameters. In this paper, a brief description of our previous work on automatic camera network design is initially reported. This semi-automatic procedure results in wide-baseline high resolution images covering an object of interest, and including approximations of image orientations, a rough 3D object geometry and a matching matrix indicating for each image its matching mates. The main part of this paper will describe the subsequent image matching where the pre-knowledge on the image orientations and the pre-created rough 3D model of the study object is exploited. Ultimately the matching information retrieved during that step will be used for a precise bundle block adjustment. Since we defined the initial image orientation in the design of the network, we can compute the matching matrix prior to image matching of high resolution images. For each image involved in several pairs that is defined in the matching matrix, we detect the corners or keypoints and then transform them into the matching images by using the designed orientation and initial 3D model. Moreover, a window is defined for each corner and its initial correspondence in the matching images. A SIFT or SURF matching is implemented between every matching window to find the homologous points. This is followed by Least Square Matching LSM to refine the correspondences for a sub-pixel localization and to avoid inaccurate matches. Image matching is followed by a bundle adjustment to orient the images automatically to finally have a sparse 3D model. We used the commercial software Photomodeler Scanner 2010 for implementing the bundle adjustment since it reports a number of accuracy indices which are necessary for the evaluation purposes. The experimental test of comparing the automated image matching of four pre-designed streopairs shows that our approach can provide a high accuracy and effective orientation when compared to the results of commercial and open source software which does not exploit the pre-knowledge about the scene.

show abstract

Expert system-based design of close-range photogrammetric networks

Cited by 34 publications

References 7 publications

Bundle Adjustment — A Modern Synthesis

Bundle Adjustment — A Modern Synthesis

<title>Experimental analysis and design considerations of virtual environments creation</title>

Robust extraction of image correspondences exploiting the image scene geometry and approximate camera orientation

Contact Info

Product

Resources

About