Abstract
Abstract. Photorealistic three-dimensional (3D) models play an indispensable role in the spatial data infrastructure (SDI) of a smart city. Recent developments in aerial oblique photogrammetry, and the popularity of terrestrial mobile mapping systems (MMSs) offer possibilities for deriving 3D models with centimeter-level accuracy in urban areas. Additionally, advances in image matching and bundle adjustment have allowed 3D models derived from the integration of aerial and ground imagery to overcome typical problems related to 3D mapping in urban areas (e.g., geometric defects, blurred textures on building façades). Nevertheless, this approach may not be suitable for all scenarios owing to innate differences between each platform. Besides, MMS images may not cover regions that cannot be reached by mobile vehicles in urban areas (e.g., narrow alleys, areas far from roads). Meanwhile, backpack systems have garnered attention from the photogrammetry community in recent years due to their flexibility, and regions neglected in previous works can be adequately reconstructed from images collected by backpack systems. This paper presents an approach for effectively integrating multi-source images collected by aerial, MMS, and backpack platforms for seamless 3D mapping in urban areas. The approach includes three main steps: (1) data pre-processing, (2) combined structure-from-motion, and (3) optimal generation of a textured 3D mesh model. The experimental results using aerial, MMS, and backpack datasets collected in a typical urban area in Hong Kong demonstrate the promising performance of the proposed approach. The described work is significant for boosting various types of imagery for integrated 3D mapping in both city scale and street level to facilitate various applications.
Highlights
With more profound recognition of 3D city data, great importance has been attached to 3D photorealistic city models because of their usage in many applications to meet the increasing demand for high geometric accuracy and improved texture (Biljecki et al, 2015; Qiao et al, 2010; Singh et al, 2013)
The mobile mapping systems (MMSs) laser scanning point clouds georeferenced based on the integrated bundle adjustment (BA) of the aerial and MMS images are used as the ground truth to evaluate the geometrical accuracy
In the alley region (Figure 7), the unsigned CMD of the mesh model derived from the unmanned aerial vehicle (UAV) images approaches 1 m at the end of the alley, which is covered by a rooftop
Summary
With more profound recognition of 3D city data, great importance has been attached to 3D photorealistic city models because of their usage in many applications to meet the increasing demand for high geometric accuracy and improved texture (Biljecki et al, 2015; Qiao et al, 2010; Singh et al, 2013). With the advent of mobile mapping systems (MMSs), closerange photogrammetry based on MMS platforms has been widely used for 3D mapping and modeling applications in urban areas. Assisted by MMSs, recent endeavors to combine oblique aerial images and terrestrial images for improved 3D modeling (Wu et al, 2018) offer 3D building models with optimum geometric accuracy and texture. Textural blurs may occur on MMS images when the vehicle moves at high speed This problem can be addressed by wearable mapping solutions, such as backpack mapping systems, which have triggered increasing interest because of their flexibility in data collection. MMS, and backpack images is an ideal solution for seamless 3D mapping in urban areas, which is desirable in terms of both the scale range and high degree of details.
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