Abstract
Abstract. This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.
Highlights
Indoor environments are essential to people’s daily life
Indoor mapping and positioning technologies have become in high demand in recent years
Many efforts have been made in the last few years to improve the SLAM algorithms (Zhang & singh, 2014a) and the geometric/semantic information extraction from point clouds and images (Armeni et al, 2016a)
Summary
Indoor environments are essential to people’s daily life. Indoor mapping and positioning technologies have become in high demand in recent years. During the IMLS procedure, 3D point clouds and high accuracy trajectories with position and orientation are acquired. Many efforts have been made in the last few years to improve the SLAM algorithms (Zhang & singh, 2014a) and the geometric/semantic information extraction from point clouds and images (Armeni et al, 2016a). There are still some challenges as follows: first, lack of efficient or real-time 3D point cloud generation methods of as-built 3D indoor environment; second, difficulties of building information model (BIM) features extraction in the clustered and occluded indoor environment. Given the relatively high accuracy, the IMLS trajectory provides a good reference or ground-truth for the lowcost indoor positioning solutions
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