Three dimensional Terrain modeling and display for environmental assessment

Kaneda, Kazufumi; Kato, Fumitake; Nakamae, Eihachiro; Nishita, Tomoyuki; Tanaka, Hideaki; Noguchi, Takao

doi:10.1145/74333.74354

Cited by 26 publications

(12 citation statements)

References 13 publications

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“…In this step, background images are generated from contour data and aerial photographs when the visual impact of newly constructed buildings is assessed by using animations. For details of the techniques involved, see (Kaneda et al 1989). Artificial objects, such as buildings, can be adequately described numerically.…”

Section: Image Creation Stepmentioning

confidence: 99%

“…2, conversion of image data from the image scanner is carried out in the data input step. Our method also supports scanned-in background pictures for montage images (Nakamae et al 1986;Kaneda et al 1989), but that is beyond the scope of this paper.…”

Section: Displaying Low-brush Thicketsmentioning

confidence: 99%

“…In order to address this prob- Fig. 1 a, h. Computer graphic images for environmental assessment lem, the authors developed an image-synthesis technique using contour data from maps combined with aerial photographs (Kaneda et al 1989). In this method, a three-dimensional terrain model is constructed from contour data, and a background image with an arbitrary viewpoint, view reference point, and view angles is generated by mapping aerial photographs onto the terrain model.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reliability of computer graphic images for visual assessment

Nakamae

Kaneda

Harada

et al. 1991

The Visual Computer

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Section: Image Creation Stepmentioning

confidence: 99%

Section: Displaying Low-brush Thicketsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reliability of computer graphic images for visual assessment

Nakamae

Kaneda

Harada

et al. 1991

The Visual Computer

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“…However, the production of realistic environments often requires the use of large textures which are uniquely applied to individual surfaces. For example, realistic urban simulations and terrain visualizations [8] may involve real photographic imagery applied to the geometry of outdoor environments. Indoor environments may be mapped with illumination data resulting from pre-computed radiosity simulations [2].…”

Section: Introductionmentioning

confidence: 99%

Uniform frequency images: adding geometry to images to produce space-efficient textures

Hunter¹,

Cohen²

Proceedings Visualization 2000. VIS 2000 (Cat. No.00CH37145)

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Abstract:We discuss the concept of uniform frequency images, which exhibit uniform local frequency properties. Such images make optimal use of space when sampled close to their Nyquist limit. A warping function may be applied to an arbitrary image to redistribute its local frequency content, reducing its highest frequencies and increasing its lowest frequencies in order to approach this uniform frequency ideal. The warped image may then be downsampled according to its new, reduced Nyquist limit, thereby reducing its storage requirements. To reconstruct the original image, the inverse warp is applied.We present a general, top-down algorithm to automatically generate a piecewise-linear warping function with this frequency balancing property for a given input image. The image size is reduced by applying the warp and then downsampling. We store this warped, downsampled image plus a small number of polygons with texture coordinates to describe the inverse warp. The original image is later reconstructed by rendering the associated polygons with the warped image applied as a texture map, a process which is easily accelerated by current graphics hardware. As compared to previous image compression techniques, we generate a similar graceful space-quality tradeoff with the advantage of being able to "uncompress" images during rendering. We report results for several images with sizes ranging from 15,000 to 300,000 pixels, achieving reduction rates of 70-90% with improved quality over downsampling alone.

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“…Animations generated by computer graphics [2] appeared with the popularization of video frame recording systems; rendering by using remote sensing [3] and terrain visibility [4] has been developed. Algorithms for saving computation time are important and an interesting subject, too, such as rendering terrain models based on fractals [5,6], polygon reduction [7], etc..…”

Section: Introductionmentioning

confidence: 99%

Computer generated still images composited with panned landscape video sequences

Nakamae

Qin²,

Jiao³

et al.

Proceedings 1998 MultiMedia Modeling. MMM'98 (Cat. No.98EX200)

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We present a novel approach to offer at a reasonable cost panned landscape video sequence images well matched with photorealistic computer generated still images of large scale construction projects, such as bridges and electric power transmission towers. Our newly developed compositing algorithms can be used with the equipment which consists of a regular camcorder sold on the market, a video editing system, and our own software for rendering daytime scenes under various weather conditions. Other types of equipment such as an elaborate camera controller, or special reference points in the landscapes, are unnecessary. The proposed algorithms provide the following features: (1) the computer generated still images are well harmonized with panned video sequence images at any time of day under various weather conditions, in terms of both optical and geometrical accuracy; (2) a precise panorama composited from video sequence images is created, in which varying exposure levels due to changing camera view fields can be coped with and any geometrical distortion is eliminated.

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Three dimensional Terrain modeling and display for environmental assessment

Cited by 26 publications

References 13 publications

Reliability of computer graphic images for visual assessment

Reliability of computer graphic images for visual assessment

Uniform frequency images: adding geometry to images to produce space-efficient textures

Computer generated still images composited with panned landscape video sequences

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