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Titlebook: Automatic Extraction of Man-Made Objects from Aerial and Space Images (II); Armin Gruen,Emmanuel P. Baltsavias,Olof Henricsson Conference

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21#
發(fā)表于 2025-3-25 04:27:26 | 只看該作者
A model driven approach to extract buildings from multi-view aerial imageryposed approach combines bottom-up and topdown processing. In this paper the emphasis is on the discussion of the experimental evaluation. To evaluate statistically the performance of the system, a set of 100 realisations of 5 images from different viewpoints was used, which was generated by combinin
22#
發(fā)表于 2025-3-25 08:07:51 | 只看該作者
23#
發(fā)表于 2025-3-25 14:15:42 | 只看該作者
24#
發(fā)表于 2025-3-25 16:02:40 | 只看該作者
On the Integration of Object Modeling and Image Modeling in Automated Building Extraction from Aeriahased on the recognition of simple building components and the successive aggregation of these building components to complete building descriptions, thereby analyzing 2D information as well as 3D information. This paper emphasizes that the modeling of the projective appearances of buildings and bui
25#
發(fā)表于 2025-3-25 23:36:43 | 只看該作者
TOBAGO — a topology builder for the automated generation of building modelsst the operator to measure the house roofs from a stereomodel in form of an unstructured point cloud. According to our experience this can be done very quickly. In a second step we fit generic building models fully automatically to these point clouds. The structure information is inherently included
26#
發(fā)表于 2025-3-26 02:34:07 | 只看該作者
Crestlines contribution to the automatic building extractioncontext of Mobile Communication Network Planning, our interest focuses on an input dataset including a stereo pair of aerial images and a DSM (Digital Surface Model) modeling all 3D objects. DSM is provided either by stereo-vision or by active sensors. In this paper, we propose to use crestlines ext
27#
發(fā)表于 2025-3-26 08:13:27 | 只看該作者
Recognizing Buildings in Aerial Imagesraphs. Depending on the level of matching, the given picture is classified as building or background. The graphs are constructed based on a learning set and using an entropy criterion to separate building images and background images by recursive partitioning. In the future we hope to extend our alg
28#
發(fā)表于 2025-3-26 09:47:12 | 只看該作者
29#
發(fā)表于 2025-3-26 13:01:01 | 只看該作者
30#
發(fā)表于 2025-3-26 19:16:12 | 只看該作者
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