Smartphone LiDAR Technologies for Surveying and Reality Modelling in Urban Scenarios: Evaluation Methods, Performance and Challenges

A Lightweight Approach to Localization for Blind and Visually Impaired Travelers

Independent wayfinding is a major challenge for blind and visually impaired (BVI) travelers. Although GPS-based localization approaches enable the use of navigation smartphone apps that provide accessible turn-by-turn directions in outdoor settings, such approaches are ineffective in indoor and other GPS-deprived settings. We build on our previous work on a localization algorithm based on computer vision and inertial sensing; the algorithm is lightweight in that it requires only a 2D floor plan of the environment, annotated with the locations of visual landmarks and points of interest, instead of a detailed 3D model (used in many computer vision localization algorithms), and requires no new physical infrastructure (such as Bluetooth beacons). The algorithm can serve as the foundation for a wayfinding app that runs on a smartphone; crucially, the approach is fully accessible because it does not require the user to aim the camera at specific visual targets, which would be problematic for BVI users who may not be able to see these targets. In this work, we improve upon the existing algorithm so as to incorporate recognition of multiple classes of visual landmarks to facilitate effective localization, and demonstrate empirically how localization performance improves as the number of these classes increases, showing the time to correct localization can be decreased by 51-59%. The source code for our algorithm and associated data used for our analyses have been made available in a free repository.

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of 3D point cloud datasets is studied, through an experimental protocol evaluation of new LiDAR sensors on smartphones. To evaluate and analyse the 3D point cloud datasets, different experimental conditions are considered depending on the acquisition mode and the type of object or surface being scanned. The conditions allowing us to obtain the most accurate data are identified and used to propose which acquisition protocol to use. This protocol seems to be the most adapted when using these LiDAR sensors to digitise complex interior buildings such as railway stations. This paper aims to propose: (i) a methodology to suggest the adaptation of an experimental protocol based on factors (distance, luminosity, surface, time, and incidence) to assess the precision and accuracy of the smartphone LiDAR sensor in a controlled environment; (ii) a comparison, both qualitative and quantitative, of smartphone LiDAR data with other traditional 3D scanner alternatives (Faro X130, VLX, and Vz400i) while considering three representative building interior environments; and (iii) a discussion of the results obtained in a controlled and a field environment, making it possible to propose recommendations for the use of the LiDAR smartphone at the end of the numerisation of the interior space of a building.