  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.

Computer Vision and Pattern Recognition;Artificial Intelligence