Ocrapose: An indoor positioning system using smartphone/tablet cameras and OCR-aided stereo feature matching
Hamed Sadeghi, Shahrokh Valaee, Shahram Shirani
Abstract
In this paper, we propose an image-based localization system, applicable for a number of indoor scenarios including office buildings, airports, chain stores, etc. In such applications, text/numbers are suitable distinctive landmarks for localization. The proposed system takes advantage of OCR to read the text/numbers and provide a rough estimate using the floor plan. Next, it performs OCR-aided stereo feature matching to refine the estimate by solving a PnP problem. Experiments show that this system achieves a median localization error of less than 50 cm for test positions located as far as 7 meters from a 20cm by 30cm number plate using different test devices in a university building scenario.
BibTeX
@inproceedings{icassp2015_ocraposeanindoor,
title = {Ocrapose: An indoor positioning system using smartphone/tablet cameras and OCR-aided stereo feature matching},
author = {Hamed Sadeghi and Shahrokh Valaee and Shahram Shirani},
booktitle = {ICASSP 2015},
year = {2015}
}