Memory-efficient real-time map building using octree of planes and points

Jo, Yong-Hyun; Jang, Hye-Young; Kim, Yeon Ho; Cho, Joon Kee; Moradi, Hadi; Han, JungHyun

doi:10.1080/01691864.2013.755248

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…To speed up the plane extraction, the methods in the following papers separate the points into cells, either grid or octree, and try to extract a plane per cell: A grid approach with RANSAC plane extraction is shown in (Hansen et al, 2006). Two similar solutions using an octree data structure are presented in (Wang and Tseng, 2004) and (Jo et al, 2013). Both try to extract a plane in one cell and divide the cell, until a sufficient solution is found.…”

Section: Related Workmentioning

confidence: 99%

Fast and Adaptive Surface Reconstruction From Mobile Laser Scanning Data of Urban Areas

Gordon

Hebel

Arens

2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The availability of 3D environment models enables many applications such as visualization, planning or simulation. With the use of current mobile laser scanners it is possible to map large areas in relatively short time. One of the emerging problems is to handle the resulting huge amount of data. We present a fast and adaptive approach to represent connected 3D points by surface patches while keeping fine structures untouched. Our approach results in a reasonable reduction of the data and, on the other hand, it preserves details of the captured scene. At all times during data acquisition and processing, the 3D points are organized in an octree with adaptive cell size for fast handling of the data. Cells of the octree are filled with points and split into subcells, if the points do not lie on one plane or are not evenly distributed on the plane. In order to generate a polygon model, each octree cell and its corresponding plane are intersected. As a main result, our approach allows the online generation of an expandable 3D model of controllable granularity. Experiments have been carried out using a sensor vehicle with two laser scanners at an urban test site. The results of the experiments show that the demanded compromise between data reduction and preservation of details can be reached.

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Section: Related Workmentioning

confidence: 99%

Fast and Adaptive Surface Reconstruction From Mobile Laser Scanning Data of Urban Areas

Gordon

Hebel

Arens

2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…To speed up the plane extraction, the methods in the following publications separate the points into cells, either grid or octree, and try to extract a plane per cell: A grid approach with RANSAC plane extraction is shown in (Hansen et al, 2006). Two similar solutions using an octree data structure are presented in (Wang and Tseng, 2004) and (Jo et al, 2013). Both try to extract a plane in one cell and divide it, until a sufficient solution is found.…”

Section: Surface Reconstructionmentioning

confidence: 99%

“…In (Wang and Tseng, 2004) least square plane fitting is used, followed by a merge-strategy during postprocessing. (Jo et al, 2013) exploit the regular pattern of the TOF camera for "microplane" estimation and check if all "microplanes" in a cell match, given an error bound.…”

Section: Surface Reconstructionmentioning

confidence: 99%

Ad Hoc Model Generation Using Multiscale Lidar Data From a Geospatial Database

Gordon

Borgmann

Gehrung

et al. 2015

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

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ABSTRACT:Due to the spread of economically priced laser scanning technology nowadays, especially in the field of topographic surveying and mapping, ever-growing amounts of data need to be handled. Depending on the requirements of the specific application, airborne, mobile or terrestrial laser scanners are commonly used. Since visualizing this flood of data is not feasible with classical approaches like raw point cloud rendering, real time decision making requires sophisticated solutions. In addition, the efficient storage and recovery of 3D measurements is a challenging task. Therefore we propose an approach for the intelligent storage of 3D point clouds using a spatial database. For a given region of interest, the database is queried for the data available. All resulting point clouds are fused in a model generation process, utilizing the fact that low density airborne measurements could be used to supplement higher density mobile or terrestrial laser scans. The octree based modeling approach divides and subdivides the world into cells of varying size and fits one plane per cell, once a specified amount of points is present. The resulting model exceeds the completeness and precision of every single data source and enables for real time visualization. This is especially supported by data compression ratios of about 90%.

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Improved lazy theta∗ algorithm based on octree map for path planning of UAV

Yuan

Zhou

2023

Defence Technology

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Memory-efficient real-time map building using octree of planes and points

Cited by 4 publications

References 6 publications

Fast and Adaptive Surface Reconstruction From Mobile Laser Scanning Data of Urban Areas

Fast and Adaptive Surface Reconstruction From Mobile Laser Scanning Data of Urban Areas

Ad Hoc Model Generation Using Multiscale Lidar Data From a Geospatial Database

Improved lazy theta∗ algorithm based on octree map for path planning of UAV

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