Preprint Article Version 1 NOT YET PEER-REVIEWED

An Original Application of Image Recognition Based Location in Complex Indoor Environment

Version 1 : Received: 14 December 2016 / Approved: 15 December 2016 / Online: 15 December 2016 (07:17:35 CET)

A peer-reviewed article of this Preprint also exists.

Chiabrando, F.; Di Pietra, V.; Lingua, A.; Cho, Y.; Jeon, J. An Original Application of Image Recognition Based Location in Complex Indoor Environments. ISPRS Int. J. Geo-Inf. 2017, 6, 56. Chiabrando, F.; Di Pietra, V.; Lingua, A.; Cho, Y.; Jeon, J. An Original Application of Image Recognition Based Location in Complex Indoor Environments. ISPRS Int. J. Geo-Inf. 2017, 6, 56.

Journal reference: ISPRS Int. J. Geo-Inf. 2017, 6, 56
DOI: 10.3390/ijgi6020056

Abstract

This paper describes the first results of an Image Recognition Based Location (IRBL) for mobile application focusing on the procedure to generate a Database of range images (RGB-D). In an indoor environment, to estimate the camera position and orientation, a prior spatial knowledge of the surrounding is needed. In order to achieve this objective a complete 3D survey of two different environment (Bangbae metro station of Seoul and E.T.R.I. building in Daejeon – Republic of Korea) was performed using LiDAR (Light Detection And Ranging) instrument and the obtained scans were processed in order to obtain a spatial model of the environments. From this, two databases of reference images were generated using a specific software realized by the Geomatics group of Politecnico di Torino (ScanToRGBDImage). This tool allow to generate synthetically different RGB-D images) centered in the each scan position in the environment. Later, the external parameters (X, Y, Z, ω, φ, κ) and the range information extracted from the DB images retrieved, are used as reference information for pose estimation of a set of acquired mobile pictures in the IRBL procedure. In this paper the survey operations, the approach for generating the RGB-D images and the IRB strategy are reported. Finally the analysis of the results and the validation test are described.

Subject Areas

image recognition bases location; indoor positioning; RGB-D images; LiDAR; DataBase; mobile computing; image retrieval

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