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Carlos Merino-Gracia and Majid Mirmehdi (2014)

Real-time text tracking in natural scenes

IET Computer Vision, 8(6):670–681.


We present a system that automatically detects, recognises and tracks text in natural scenes in
real-time. The focus of our method is on large text found in outdoor environments, such as shop
signs, street names, billboards and so on. Built on top of our previously developed techniques for
scene text detection and orientation estimation, the main contribution of this work is to present a
complete end-to-end scene text reading system based around text tracking. We propose to use a set
of Unscented Kalman Filters (UKF) to maintain each text region’s identity and to continuously
track the homography transformation of the text into a fronto-parallel view, thereby being resilient
to erratic camera motion and wide baseline changes in orientation. The system is designed for
continuous, unsupervised operation in a handheld or wearable system over long periods of time. It
is completely automatic and features quick failure recovery and interactive text reading. It is also
highly parallelised to maximize usage of available processing power and achieve real-time operation.
We demonstrate the performance of the system on sequences recorded in outdoor scenarios.


This work is part of our project to develop a text reading system for blind people.

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