Linear building pattern recognition combining Gestalt principles and convex polygon decomposition

被引：0

作者：

Wei Z. ^{[1
,2
]}

Ding S. ^{[3
]}

Tong Y. ^{[4
]}

Cheng L. ^{[4
]}

Liu Y. ^{[4
]}

机构：

[1] Key Laboratory of Network Information System Technology, Institute of Electronic, Chinese Academy of Sciences, Beijing

[2] Aerospace Information Research Institute, Chinese Academic of Sciences, Beijing

[3] College of Environmental and Resource Science, Hangzhou

[4] School of Resources and Environment Science, Wuhan University, Wuhan

来源：

Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2023年 / 52卷 / 01期

基金：

中国国家自然科学基金;

关键词：

building; convex decomposition; Gestalt principles; linear pattern; spatial distribution;

D O I：

10.11947/j.AGCS.2023.20210286

中图分类号：

学科分类号：

摘要：

Building patterns are important local structures characterizing urban areas. Building patterns in previous studies are mostly recognized based on the Gestalt principles in which buildings are considered as a whole. However, human vision is also proved as a parts-based system, and some visually aware patterns may fail to be recognized with the existing methods. This paper first combines Gestalt principles and the convex polygon decomposition to recognize linear patterns. First, the linear patterns are defined based on the triples and Gestalt principles. Second, linear patterns are recognized combining the convex polygon decomposition, and the buildings' orthogonal features are considered in their decomposition. The experimental results show that proposed method is effective to recognize the linear patterns in study area. Compared with the existing methods, the accuracy and recall have increased by 15.7% and 30.5%, respectively. © 2023 SinoMaps Press. All rights reserved.

引用

页码：117 / 128

页数：11

共 39 条

[1] LIU Huimin, HU Wenke, TANG Jianbo, Et al., A method for recognizing building clusters by considering functional features of buildings, Acta Geodaetica et Cartographica Sinica, 49, 5, pp. 622-631, (2020)
[2] ZHANG Xiuyuan, DU Shihong, WANG Yichen, Semantic classification of heterogeneous urban scenes using intrascene feature similarity and interscene semantic dependency, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 5, pp. 2005-2014, (2015)
[3] DU Shihong, ZHANG Fangli, ZHANG Xiuyuan, Semantic classification of urban buildings combining VHR image and GIS data: an improved random forest approach, ISPRS Journal of Photogrammetry and Remote Sensing, 105, pp. 107-119, (2015)
[4] MAO Bo, HARRIE L, BAN Yifang, Detection and typification of linear structures for dynamic visualization of 3D city models, Computers, Environment and Urban Systems, 36, 3, pp. 233-244, (2012)
[5] ZHANG Liqiang, DENG Hao, CHEN Dong, Et al., A spatial cognition-based urban building clustering approach and its applications, International Journal of Geographical Information Science, 27, 4, pp. 721-740, (2013)
[6] RUAS A, HOLZAPFEL F., Automatic characterisation of building alignments by means of expert knowledge, Proceedings of the 21st International Cartographic Conference (ICC), pp. 1604-1616, (2003)
[7] STEINIGER S., Enabling pattern-aware automated map generalization, (2007)
[8] ZHANG Xiang, STOTER J, AI Tinghua, Et al., Automated evaluation of building alignments in generalized maps, International Journal of Geographical Information Science, 27, 8, pp. 1550-1571, (2013)
[9] RENARD J, DUCHENE C., Urban structure generalization in multi-agent process by use of reactional agents, Transactions in GIS, 18, 2, pp. 201-218, (2014)
[10] ANDERS K H, SESTER M., A hierarchical graph-clustering approach to find groups of objects, Proceedings of the 5th Workshop on Progress in Automated Map Generalization, (2003)

← 1 2 3 4 →