An Efficient Encoding Voxel-Based Segmentation (EVBS) Algorithm Based on Fast Adjacent Voxel Search for Point Cloud Plane Segmentation

Huang, Ming; Wei, Pengcheng; Liu, Xianglei

doi:10.3390/rs11232727

Cited by 39 publications

(32 citation statements)

References 35 publications

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“…Filtering the pavement in the road scene can reduce the amount of data and improve the efficiency and accuracy of guardrail identification. This paper employs an EVBS with improved efficiency (10) to segment the pavement: we change the seed selection strategy and regional growing conditions to adapt to the pavement segmentation. Firstly, the voxel height, number of points, and flatness are used as seed selection factors.…”

Section: Pavement Removalmentioning

confidence: 99%

“…Voxelization of point clouds. First, we set the voxel size d I , and then use the efficient binary ecoding method (10) to construct the octree for the point cloud and complete the voxelization of the off-ground point cloud, as shown in Fig. 3(a).…”

Section: Voxelization Clustering Segmentation Of Off-ground Pointsmentioning

confidence: 99%

“…Most of the methods based on a laser point cloud are overreliant on the scanning line information and only recognize a small amount of real-time point cloud data, and they cannot effectively distinguish concrete and steel guardrails on the highway. To overcome the above defects, in this paper, we apply an improved efficient binary ecoding voxel plane segmentation algorithm (EVBS) based on the voxel segmentation of a point cloud (10) to filter out the pavement and reduce the data volume, and then a voxel Euclidean clustering point cloud segmentation method is proposed to improve the efficiency of clustering. The slicing method combined with the geometric space characteristics of the guardrail is used to extract the guardrail from the clustered target.…”

Section: Introductionmentioning

confidence: 99%

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Expressway Guardrail Extraction and Classification Based on Slice Method

Huang¹,

Zhou²,

Pengpeng³

et al. 2020

Sensors and Materials

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Guardrails are an important ancillary facility of expressways. Accurate and effective identification of guardrails from road scenes plays an important role in high-precision map construction, automatic driving, road maintenance, and so on. At present, there are few research methods on guardrail recognition in highway scenes, and the existing methods have some defects such as low recognition accuracy and inability to distinguish guardrail types. In this paper, a point cloud of an expressway scene obtained by mobile laser scanning is taken as the research object. On the basis of the binary coding voxelization segmentation method, the clustering slicing method is used to recognize the guardrail target in the expressway scene according to the characteristics of the guardrail. In addition, a method for distinguishing the type of guardrail based on its cross-section characteristics is proposed to distinguish steel and concrete guardrails in a highway. The experimental results show that the proposed method can effectively identify the guardrail target in the point cloud of an expressway scene, and has high efficiency and accuracy.

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Section: Pavement Removalmentioning

confidence: 99%

Section: Voxelization Clustering Segmentation Of Off-ground Pointsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Expressway Guardrail Extraction and Classification Based on Slice Method

Huang¹,

Zhou²,

Pengpeng³

et al. 2020

Sensors and Materials

Self Cite

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“…In order to follow more closely the point cloud, the coordinates exported for each node are not those of the center of the corresponding voxel, but those of the center of mass of the points contained in the voxel (Huang et al, 2019).…”

Section: Skeleton Extractionmentioning

confidence: 99%

Modelling a Cell Tower Using Sfm: Automated Detection of Structural Elements From Skeleton Extraction on a Point Cloud

Deidda

Pala

Sanna

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The surveying and management of telecommunication towers poses a series of engineering challenges. Not only they must be regularly inspected for the purpose of checking for issues that require maintenance interventions, but they are often sub-let by their owners to communication companies, requiring a survey of the many (several thousand per company) installed appliances to check that they respect the established contracts. This requires a surveying methodology that is fast and possibly automated. Photogrammetric techniques using UAV-mounted cameras seem to offer a solution that is both suitable and economical. Our research team was asked to evaluate whether, from the information acquired by small drones it was possible to obtain geometric information on the structure, with what degree of accuracy and what level of detail. The workflow of this process is naturally articulated in three steps: the acquisition, the construction of the point cloud, and the extraction of geometries. The case study is a tower carrying antennas owned by several operators and placed in the industrial district of Cagliari. The article examines the problems found in modelling such structures using point clouds derived from the Structure-from-Motion technique, in order to obtain a model of nodes and beams suitable for the reconstruction of the structure’s geometric elements, and possibly for a finite elements analysis or for populating GIS and BIM, either automatically or with minimal user intervention. In order to achieve this, we have used voxelization and skeleton extraction algorithms to obtain a 3D graph of the structure. The analysis of the results was carried out by varying the parameters relating to the voxel size, which defines the resolution, and the density of the points contained inside each voxel.

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“…The runtime of the classical marching cube algorithm depends significantly on the number of voxels considered. An optimisation is based on the hierarchical investigation beforehand, as described, to use only voxels as input that contain points and thus represent an object [ 8 , 17 ].…”

Section: Generation Of Geo-referenced Point Cloudsmentioning

confidence: 99%

Constructing Geo-Referenced Virtual City Models from Point Cloud Primitives

Fricke

Asche

2020

Computational Science and Its Applications – ICCSA 2020

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This paper presents a novel approach to construct spatially-referenced, multidimensional virtual city models from remotely generated point clouds for areas that lack reliable geographical reference data. A multidimensional point cloud is an unstructured array of single, irregular points in a spatial 3D coordinate system plus time stamp. If geospatial reference points are available, a point cloud is geo-referenced. Geo-referenced point clouds contain a high-precision reference dataset. Point clouds can be utilised in a variety of applications. They are particularly suitable for the representation of surfaces, structures, terrain and objects. Point clouds are used here to generate a virtual 3D city model representing the complex, granular cityscape of Jerusalem and its centre, the Old City. The generation of point clouds is based on two data acquisition methods: active data capture by laser scanning and passive data collection by photogrammetric methods. In our case, very high-resolution stereo imagery in visible light and near infrared bands have been systematically acquired an aerial flight campaign. The spatio-temporal data gathered necessitate further processing to extract the geographical reference and semantic features required in a specific resolution and scale. An insight is given into the processing of an unstructured point cloud to extract and classify the 3D urban fabric and reconstruct its objects. Eventually, customised, precise and up-to-date geographical datasets can be made available for a defined region at a defined resolution and scale.

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An Efficient Encoding Voxel-Based Segmentation (EVBS) Algorithm Based on Fast Adjacent Voxel Search for Point Cloud Plane Segmentation

Cited by 39 publications

References 35 publications

Expressway Guardrail Extraction and Classification Based on Slice Method

Expressway Guardrail Extraction and Classification Based on Slice Method

Modelling a Cell Tower Using Sfm: Automated Detection of Structural Elements From Skeleton Extraction on a Point Cloud

Constructing Geo-Referenced Virtual City Models from Point Cloud Primitives

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