找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

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

[復(fù)制鏈接]
樓主: 磨損
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
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-8 18:55
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
绵竹市| 团风县| 许昌市| 噶尔县| 长宁县| 进贤县| 睢宁县| 泊头市| 内丘县| 陆良县| 新昌县| 庆城县| 林周县| 安平县| 日照市| 布尔津县| 兴文县| 山丹县| 大安市| 盐源县| 庄河市| 仁化县| 两当县| 陈巴尔虎旗| 樟树市| 衡山县| 越西县| 龙陵县| 遵化市| 青田县| 岳阳县| 曲靖市| 光山县| 名山县| 古蔺县| 西华县| 文水县| 景谷| 吴忠市| 阿克| 岳池县|