An adaptive approach for the segmentation and extraction of planar and linear/cylindrical features from laser scanning data

Lari, Zahra; Habib, Ayman

doi:10.1016/j.isprsjprs.2013.12.001

Cited by 68 publications

(45 citation statements)

References 18 publications

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“…However, the majority of these techniques do not take the internal characteristics of laser scanning data-i.e., local point density variations and noise level in data-into account [8]. In order to overcome this limitation, an adaptive approach for the segmentation and extraction of planar surfaces, proposed by [46], is employed in this research. This approach is implemented while considering the possibility of application to multi-platform laser scanning datasets and considers local point density variations and random errors within datasets.…”

Section: Laser Scanning Data Segmentation and Planar Feature Extractionmentioning

confidence: 99%

“…In this approach, the coordinates of normal projections of an arbitrary origin to the best-fitted planes to locally-classified planar neighborhoods are defined as segmentation attributes [46]. The coordinates of these attribute points are computed based on the precisely-estimated parameters representing these neighborhoods.…”

Section: Segmentation Attributes Computationmentioning

confidence: 99%

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A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

2017

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Abstract:Over the past few years, accurate 3D surface reconstruction using remotely-sensed data has been recognized as a prerequisite for different mapping, modelling, and monitoring applications. To fulfill the needs of these applications, necessary data are generally collected using various digital imaging systems. Among them, laser scanners have been acknowledged as a fast, accurate, and flexible technology for the acquisition of high density 3D spatial data. Despite their quick accessibility, the acquired 3D data using these systems does not provide semantic information about the nature of scanned surfaces. Hence, reliable processing techniques are employed to extract the required information for 3D surface reconstruction. Moreover, the extracted information from laser scanning data cannot be effectively utilized due to the lack of descriptive details. In order to provide a more realistic and accurate perception of the scanned scenes using laser scanning systems, a new approach for 3D reconstruction of planar surfaces is introduced in this paper. This approach aims to improve the interpretability of the extracted planar surfaces from laser scanning data using spectral information from overlapping imagery collected onboard modern low-cost aerial mapping systems, which are widely adopted nowadays. In this approach, the scanned planar surfaces using laser scanning systems are initially extracted through a novel segmentation procedure, and then textured using the acquired overlapping imagery. The implemented texturing technique, which intends to overcome the computational inefficiency of the previously-developed 3D reconstruction techniques, is performed in three steps. In the first step, the visibility of the extracted planar surfaces from laser scanning data within the collected images is investigated and a list of appropriate images for texturing each surface is established. Successively, an occlusion detection procedure is carried out to identify the occluded parts of these surfaces in the field of view of captured images. In the second step, visible/non-occluded parts of the planar surfaces are decomposed into segments that will be textured using individual images. Finally, a rendering procedure is accomplished to texture these parts using available images. Experimental results from overlapping laser scanning data and imagery collected onboard aerial mapping systems verify the feasibility of the proposed approach for efficient realistic 3D surface reconstruction.

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Section: Laser Scanning Data Segmentation and Planar Feature Extractionmentioning

confidence: 99%

Section: Segmentation Attributes Computationmentioning

confidence: 99%

A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

2017

Self Cite

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“…In this paper, the parameter-domain segmentation approach proposed by (Lari and Habib, 2014) is utilized for the extraction of planar regions from laser scanning data. In the first step of this segmentation approach, a Principal Component Analysis (PCA) of local neighborhoods of individual laser scanning points is performed to detect and model potential planar neighborhoods within the laser scanning point cloud (Pauly et al, 2002).…”

Section: Planar Features Segmentationmentioning

confidence: 99%

A New Approach for Segmentation-Based Texturing of Laser Scanning Data

Lari

Habib

2015

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

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ABSTRACT:In recent years, laser scanning systems have been recognized as a fast and accurate technology for the acquisition of high density spatial data. The advent of these systems has reduced the cost and increased the availability of accurate 3D data for mapping, modelling, and monitoring applications. The original laser scanning data does not explicitly provide meaningful information about the characteristics of the scanned surfaces. Therefore, reliable processing procedures are applied for information extraction from these datasets. However, the derived surfaces through laser scanning data processing cannot be effectively interpreted due to the lack of spectral information. To resolve this problem, a new texturing procedure is introduced in this paper to improve the interpretability of laser scanning-derived surfaces using spectral information from overlapping imagery. In this texturing approach, individual planar regions, derived through a laser scanning data segmentation procedure, are textured using the available imagery. This texturing approach, which aims to overcome the computational inefficiency of the previously-developed point-based texturing techniques, is implemented in three steps. In the first step, the visibility of the segmented planar regions in the available imagery is checked and a list of appropriate images for texturing each planar region is established. An occlusion detection procedure is then performed to identify the parts of the segmented regions which are occluding/being occluded by other regions in the field of view of the utilized images. In the second step, visible parts of planar regions are decomposed into parts which should be textured using individual images. Finally, a rendering procedure is performed to texture these parts using available images. Experimental results from real laser scanning dataset and overlapping imagery demonstrate the feasibility of the proposed approach for texturing laser scanningderived surfaces using images.

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“…The proposed sequential clustering procedure is initiated in a two-dimensional directional attribute subspace. A brute-force peak detection approach (Lari and Habib, 2014) is then carried out to find clusters in directional attribute subspace, while considering the estimated clusters' extent ( Figure 5). For each of the detected clusters of attribute points in the directional attribute subspace (representing parallel pole-like features in the spatial domain), the clusters of attributes in the positional kd-tree structure are then identified to discriminate and extract individual pole-like features ( Figure 6).…”

Section: Parameter-domain Segmentation Of Pole-like Featuresmentioning

confidence: 99%

Performance of parameter-domain and spatial-domain pole-like feature segmentation using single and multiple terrestrial laser scans

Lari

Al-Durgham

Habib

2014

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

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ABSTRACT:Terrestrial laser scanning (TLS) systems have been established as a leading tool for the acquisition of high density three-dimensional point clouds from physical objects. The collected point clouds by these systems can be utilized for a wide spectrum of object extraction, modelling, and monitoring applications. Pole-like features are among the most important objects that can be extracted from TLS data especially those acquired in urban areas and industrial sites. However, these features cannot be completely extracted and modelled using a single TLS scan due to significant local point density variations and occlusions caused by the other objects. Therefore, multiple TLS scans from different perspectives should be integrated through a registration procedure to provide a complete coverage of the pole-like features in a scene. To date, different segmentation approaches have been proposed for the extraction of pole-like features from either single or multiple-registered TLS scans. These approaches do not consider the internal characteristics of a TLS point cloud (local point density variations and noise level in data) and usually suffer from computational inefficiency. To overcome these problems, two recently-developed PCA-based parameter-domain and spatial-domain approaches for the segmentation of pole-like features are introduced, in this paper. Moreover, the performance of the proposed segmentation approaches for the extraction of pole-like features from a single or multiple-registered TLS scans is investigated in this paper. The alignment of the utilized TLS scans is implemented using an Iterative Closest Projected Point (ICPP) registration procedure. Qualitative and quantitative evaluation of the extracted pole-like features from single and multiple-registered TLS scans, using both of the proposed segmentation approaches, is conducted to verify the extraction of more complete pole-like features using multipleregistered TLS scans.

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An adaptive approach for the segmentation and extraction of planar and linear/cylindrical features from laser scanning data

Cited by 68 publications

References 18 publications

A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

A New Approach for Segmentation-Based Texturing of Laser Scanning Data

Performance of parameter-domain and spatial-domain pole-like feature segmentation using single and multiple terrestrial laser scans

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