A multi‐scale partitioning and aggregation method for large volumes of buildings considering road networks association constraints

2021 ◽  
Author(s):  
Chengming Li ◽  
Wei Wu ◽  
Yong Yin ◽  
Pengda Wu ◽  
Zheng Wu
Keyword(s):  
Road Networks ◽  
Aggregation Method ◽  
Multi Scale

Multiscale Convolutional Descriptor Aggregation for Visual Place Recognition

2020 ◽  
Vol 2020 (10) ◽  
pp. 313-1-313-7
Author(s):  
Raffaele Imbriaco ◽  
Egor Bondarev ◽  
Peter H.N. de With
Keyword(s):  
Image Matching ◽  
Large Scale ◽  
Place Recognition ◽  
Aggregation Method ◽  
Local Descriptors ◽  
Multi Scale ◽  
Vector Construction ◽  
Visual Place Recognition ◽  
Different Sources ◽  
Geometric Verification

Visual place recognition using query and database images from different sources remains a challenging task in computer vision. Our method exploits global descriptors for efficient image matching and local descriptors for geometric verification. We present a novel, multi-scale aggregation method for local convolutional descriptors, using memory vector construction for efficient aggregation. The method enables to find preliminary set of image candidate matches and remove visually similar but erroneous candidates. We deploy the multi-scale aggregation for visual place recognition on 3 large-scale datasets. We obtain a Recall@10 larger than 94% for the Pittsburgh dataset, outperforming other popular convolutional descriptors used in image retrieval and place recognition. Additionally, we provide a comparison for these descriptors on a more challenging dataset containing query and database images obtained from different sources, achieving over 77% Recall@10.

scholarly journals Benchmark analysis for robustness of multi-scale urban road networks under global disruptions

2020 ◽  
Author(s):  
Wen-Long Shang ◽  
Yanyan Chen ◽  
Huibo Bi ◽  
Nicolò Daina ◽  
Washington Ochieng
Keyword(s):  
Road Networks ◽  
Benchmark Analysis ◽  
Urban Road ◽  
Multi Scale

scholarly journals Topology Conflict Detection Considering Incremental Updating of Multi-Scale Road Networks

2021 ◽  
Vol 10 (10) ◽  
pp. 655
Author(s):  
Jianchen Zhang ◽  
Jiayao Wang ◽  
Heying Li
Keyword(s):  
Road Networks ◽  
Recall Rate ◽  
Detection Algorithm ◽  
Conflict Detection ◽  
Incremental Updating ◽  
K Value ◽  
Multi Scale ◽  
Single Scale ◽  
Detection Rule ◽  
Multiscale Networks

Incremental updating is an important technical method used to maintain the data of road networks. Topology conflict detection of multiscale road networks in incremental updating is an important link. Most of the previous algorithms focus on a single scale road network, which cannot be applied to topology conflict detection for different scale road networks during incremental updating. Therefore, this study proposes a topology conflict detection algorithm that considers the incremental updating of multiscale networks. The algorithm designs a K-order topological neighborhood to judge incremental neighborhood links and builds a topology refinement model based on geometric measurement. Furthermore, we propose a network topology conflict detection rule considering the influence of cartographic generalization operator and use the improved topological distance to detect topology conflicts. The experimental results show that (1) the overall accuracy and recall rate of the proposed method are more than 90%; (2) after considering the topology conflict caused by cartography generalization, the accuracy was increased by 29.2%; and (3) the value of average path length of a network can be used as the basis for setting the best K value.

A spatial multi-scale object to analyze road networks

2015 ◽  
Vol 3 (1) ◽  
pp. 156-181 ◽  
Author(s):  
C. LAGESSE ◽  
P. BORDIN ◽  
S. DOUADY
Keyword(s):  
Historical Development ◽  
Road Network ◽  
Geographical Origin ◽  
Road Networks ◽  
Construction Method ◽  
Town Planning ◽  
Local Geometry ◽  
Social Significance ◽  
The Road ◽  
Multi Scale

AbstractCity road networks have been extensively studied for their social significance or to quantify their connections and centralities, but often their geographical origin is forgotten. This work focuses on the spatial-geographical and geometrical aspects of the road network skeleton. Following previous work, a multi-scale object, the way, is constructed, based only on the local geometry at road crossings. The best method to reconstruct significant elements is investigated. The results show that this object is geographically meaningful, with many particular characteristics. A new indicator, structurality, is introduced and compared with previous indicators, on the cities of Paris and Avignon. Structurality appears to be stable over the borders of the map sample, and is able to reveal the underlying coherence of the road network. This stability can be interpreted as coming from the particular way the network developed in time, and was later preserved. This link with the historical development of the cites, which deserves to be further studied, is exemplified in the cases of Villers-sur-Mer (France) and Manaus (Brazil). The construction method, the results, and their potential meaning are discussed in detail so that they can be used in various related disciplines, such as sociology, town planning, geomatics, and physics.

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