Computing concave hull with closed curve smoothing: performance, concaveness measure and applications

Kalinina, Darina; Ingilevich, Varvara; Lantseva, Anastasiia; Ivanov, Sergei Evgenievich

doi:10.1016/j.procs.2018.08.258

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…There are algorithms for points in the literature in two, three, and even Euclidean spaces of higher dimension [ 36 ]. The concave hull is an algorithm that finds a concave object that surrounds all points, using methods such as Alpha Shapes or K-nearest neighbor algorithms [ 37 ]. Figure 2 shows both algorithms at points in a reconstruction, looking at only one height of the entire reconstruction.…”

Section: Proposed Frameworkmentioning

confidence: 99%

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

Biundini

Pinto

Melo

et al. 2021

Sensors

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Different practical applications have emerged in the last few years, requiring periodic and detailed inspections to verify possible structural changes. Inspections using Unmanned Aerial Vehicles (UAVs) should minimize flight time due to battery time restrictions and identify the terrain’s topographic features. In this sense, Coverage Path Planning (CPP) aims at finding the best path to coverage of a determined area respecting the operation’s restrictions. Photometric information from the terrain is used to create routes or even refine paths already created. Therefore, this research’s main contribution is developing a methodology that uses a metaheuristic algorithm based on point cloud data to inspect slope and dams structures. The technique was applied in a simulated and real scenario to verify its effectiveness. The results showed an increasing 3D reconstructions’ quality observing optimizing photometric and mission time criteria.

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Section: Proposed Frameworkmentioning

confidence: 99%

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

Biundini

Pinto

Melo

et al. 2021

Sensors

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“…In the application of GIS, in order to judge the accuracy of objects, a convex hull was used to highlight boundary characteristics of objects, especially in the description of three-dimensional objects [31]. In addition, many applications must interact with users through a GIS interface.…”

Section: Integrated Computation and Geo-information Applicationsmentioning

confidence: 99%

Using Intelligent Clustering to Implement Geometric Computation for Electoral Districting

Hung

Chen

2019

IJGI

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Traditional electoral districting is mostly carried out by artificial division. It is not only time-consuming and labor-intensive, but it is also difficult to maintain the principles of fairness and consistency. Due to specific political interests, objectivity is usually distorted and controversial in a proxy-election. In order to reflect the spirit of democracy, this study uses computing technologies to automatically divide the constituency and use the concepts of “intelligent clustering” and “extreme arrangement” to conquer many shortcomings of traditional artificial division. In addition, various informational technologies are integrated to obtain the most feasible solutions within the maximum capabilities of the computing system, yet without sacrificing the global representation of the solutions. We take Changhua County, Taiwan as an example of complete electoral districting, and find better results relative to the official version, which obtained a smaller difference in the population of each constituency, more complete and symmetrical constituencies, and fewer regional controversies. Our results demonstrate that multidimensional algorithms using a geographic information system could solve many problems of block districting to make decisions based on different needs.

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Towards rapid and automated vulnerability classification of concrete buildings

Iturburu

Kwannandar

Dyke

et al. 2023

Earthq. Eng. Eng. Vib.

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With the overwhelming number of older reinforced concrete buildings that need to be assessed for seismic vulnerability in a city, local governments face the question of how to assess their building inventory. By leveraging engineering drawings that are stored in a digital format, a well-established method for classification reinforced concrete buildings with respect to seismic vulnerability, and machine learning techniques, we have developed a technique to automatically extract quantitative information from the drawings to classify vulnerability. Using this technique, stakeholders will be able to rapidly classify buildings according to their seismic vulnerability and have access to information they need to prioritize a large building inventory. The approach has the potential to have significant impact on our ability to rapidly make decisions related to retrofit and improvements in our communities. In the Los Angeles County alone it is estimated that several thousand buildings of this type exist. The Hassan index is adopted here as the method for automation due to its simple application during the classification of the vulnerable reinforced concrete buildings. This paper will present the technique used for automating information extraction to compute the Hassan index for a large building inventory.

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Computing concave hull with closed curve smoothing: performance, concaveness measure and applications

Cited by 5 publications

References 7 publications

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

Using Intelligent Clustering to Implement Geometric Computation for Electoral Districting

Towards rapid and automated vulnerability classification of concrete buildings

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