OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images

TL;DR

OCRAPOSE II is an indoor localization system that uses OCR to identify characters as landmarks, estimating position by analyzing images and refining results with novel formulas for depth and angle-of-view, outperforming existing benchmarks.

Contribution

The paper introduces a novel OCR-based indoor positioning approach that estimates depth and angle-of-view from images, improving localization accuracy in sparse database scenarios.

Findings

Higher location recognition rate than benchmarks

Lower average localization error

Effective in various indoor environments

Abstract

In this paper, we propose an OCR (optical character recognition)-based localization system called OCRAPOSE II, which is applicable in a number of indoor scenarios including office buildings, parkings, airports, grocery stores, etc. In these scenarios, characters (i.e. texts or numbers) can be used as suitable distinctive landmarks for localization. The proposed system takes advantage of OCR to read these characters in the query still images and provides a rough location estimate using a floor plan. Then, it finds depth and angle-of-view of the query using the information provided by the OCR engine in order to refine the location estimate. We derive novel formulas for the query angle-of-view and depth estimation using image line segments and the OCR box information. We demonstrate the applicability and effectiveness of the proposed system through experiments in indoor scenarios. It is shown that our system demonstrates better performance compared to the state-of-the-art benchmarks in terms of location recognition rate and average localization error specially under sparse database condition.