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1

Wide-angle vision for road views

Huang F., Fehrs K. K., Hartmann G., Klette R.

Opto-Electronics Review

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2013

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Vol. 21, No. 1

1-22

EN

The field-of-view of a wide-angle image is greater than (say) 90 degrees, and so contains more information than available in a standard image. A wide field-of-view is more advantageous than standard input for understanding the geometry of 3D scenes, and for estimating the poses of panoramic sensors within such scenes. Thus, wide-angle imaging sensors and methodologies are commonly used in various road-safety, street surveillance, street virtual touring, or street 3D modelling applications. The paper reviews related wide-angle vision technologies by focusing on mathematical issues rather than on hardware.

2

Geometries of Panoramic Images and 3D Vision

Huang F., Torii A., Klette R.

Machine Graphics and Vision

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2010

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Vol. 19, No. 4

463-477

EN

Over the recent years, the image sensor technology has provided tools for wide-angle and high-resolution 3D recording, analysis and modeling of static or dynamic scenes, ranging from small objects, such as artifacts in a museum, to large-scale 3D models of castles or 3D city maps, also allowing real time 3D data acquisition from a moving platform, e.g. in vision-based driver assistance. More recently, due to the rapidly evolving and improving stereoscopic display technology, many of these panoramic image applications have started to contribute to stereo visualization, thus increasing realistic and immersive appearances. This paper introduces a methodology for stereo panorama acquisition and provides detailed technologies of mapping between different forms of panoramic images. Image examples illustrate the potential for projects in arts, science and technology.

3

Determination of geometric parameters for steroscopic pamorama cameras

Wei S. K., Huang F., Klette R.

Machine Graphics and Vision

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2001

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Vol. 10, No. 3

399-427

EN

This paper proposes as approach to solving the parameter determination problem for a stereoscopic pamorama camera. The image acquisition parameters have to be calculated under given constraints defined by application requirements, the image acquisition model, and specifications of the targeted 3D scenes. Previous studies on stereoscopic panorama imaging, such as [3,6,24,28,33,39,43,45], have paid great attention on how a proposed imaging approach supports a chosen area of application. The image acquisition parameter determination problem has not yet been dealt with in these studies. The lack of guigance in selecting the image acquisition parameters affects the validity of results obtained for subsequent procesess, [36]. Our approach towards parameter determination allows satisfying the common requirements of 3D scene visualization or reconstruction applications: a proper scene composition in the resultant images; an adequate sampling at a particular scene distance; and the desired stereo quality (i.e. depth levels) over diverse of scenes of interest. The paper details the models, constraints and criteria used for solving the parameter determination problem. Some practical examples are given in order to demonstrate the use of the formulas derived. The error analysis of our determonation approach is also carried out and elaborated in this paper. The study contributes to the design of stereoscopic panorama cameras as well as to manuals for on--sie image acquistion. The results of our studies are also useful for camera calibration, or pose estimation in stereoscopic panoramic imaging.

4

The length of digital curves

Klette R., Yip B.

Machine Graphics and Vision

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2000

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Vol. 9, No. 3

673-703

EN

The aper discusses one of the elementary subjects in image analysis: how to measure the lenght of a digital curve. A digital curve in the plane is defined to be a cycle given either as an alternating sequence of vertices and edges, or an alternating sequence of edges and squares. The paper reports about two lenght estimators, one based on the partition of a frontier of a simply-connected isothetic polygon into digital straight segments, and one based on calculating the minimum-lenght polygon within an open boundary of a simply-connected isothetic polygon. Both techniques are known to be implementations of covergent estimators of the perimeter of bounded, polygonal or smooth convex sets in the euclidean plane. For each technique a linear-time algorithm is specified, and both algorithms are compared with respect to convergence speed and number of generated segments. The experiments show convergent behavior also for perimeters of non-convex bounded subsets of the euclidean plane.