A canonical time warping algorithm for building shape similarity measurement

被引：0
|
作者：
Li J. [1 ,2 ,3 ]
Mao K. [2 ,3 ]
机构：
[1] Faculty Geomatics, Lanzhou Jiaotong University, Lanzhou
[2] School of Resource and Environmental Sciences, Wuhan University, Wuhan
[3] Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen
来源：
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2023年 / 52卷 / 12期
基金：
中国国家自然科学基金;
关键词：
buildings; canonical time warping? spatial cognition; shape similarity;
D O I：
10.11947/J.AGCS.2023.20220539
中图分类号：
学科分类号：
摘要：
This paper proposes a shape similarity measurement model based on canonical time warping (CTW) algorithm. The model combines canonical correlation analysis (CCA) and dynamic time warping (DTW) to align building coordinate sequences with different number of vertices, which can comprehensively evaluate the shape similarity between different shape contours. This method directly uses vector coordinates as model input without constructing complex shape coding and considers the original contour features of building shapes, which can be applied efficiently to shape retrieval and other scenarios. Experiments show that CTW algorithm is invariant to translation, rotation, scaling and mirroring when used to measure the similarity of geometric objects, and can effectively measure the shape similarity between building shapes. The results are consistent with human spatial visual cognition. © 2023 SinoMaps Press. All rights reserved.
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页码：1 / 2
页数：1
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