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

Abstract

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.

System Considerations and Challendes in 3d Mapping and Modeling Using Low-Cost Uav Systems

“…The processed and simplified point cloud can finally be textured to provide a photo-realistic visualization and semantic information pertaining to individual scanned objects. Recently, region-based texturing techniques have been introduced that make the quality of final reconstructed surfaces (data processing products) independent of point density of the utilized point cloud (Lari and Habib, 2015). Figure 4 shows a 3D photorealistic model generated using a region-based texturing technique.…”

“…In addition, the image and point cloud data can be used to derive an accurate true ortho-photo mosaic, which will be obtained by simply projecting the colored point cloud on a specified datum (Ahmar et al, 1998;Habib et al, 2007). Different from the traditional true ortho-photos, which are produced by projecting the image data onto a horizontal datum, novel techniques have been developed to generate true orthophotos relative to any datum that will be specified by the users (Lari and Habib, 2015). These products provide a valuable source of information for different mapping, modelling and monitoring applications.…”

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

“…This texturing procedure, which is an extension of the research work presented in [55], aims to integrate image-based descriptive details and laser scanning-based positional information and provide an accurate and realistic perception of the scanned planar surfaces. As a prerequisite for this procedure, the acquired laser scanning datasets and overlapping imagery are firstly registered relative to a common reference frame to ensure accurate integration of these two data sources.…”

“…The drawback of this occlusion detection procedure is its computational inefficiency when dealing with massive number of the points aggregated in the visible part/parts of planar surfaces. In order to avoid this shortcoming, a novel procedure for occlusion detection is presented in this subsection [55]. In this procedure, the occluded part/parts of a visible planar surface is/are specified based on visibility analysis of its/their inner and outer boundary points.…”

“…Hence, a new procedure for decomposition of the visible parts of planar surfaces into the segments that will be textured using the individual images is introduced in this subsection [55]. In order to accurately texture visible parts of planar surfaces within the acquired images, two different scenarios will be considered in this subsection: In summary, to identify visible parts of a planar surface in an image, one should sequentially trace the points along the image footprint intersection with that surface, its visible boundary points, and the internal points occluded by the boundary points of the other surfaces.…”