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• W1973557579 abstract "The authors present a system that automatically detects, recognises and tracks text in natural scenes in real‐time. The focus of the author's method is on large text found in outdoor environments, such as shop signs, street names, billboards and so on. Built on top of their 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 on text tracking. They propose to use a set of unscented Kalman filters 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 maximise usage of available processing power and achieve real‐time operation. They demonstrate the performance of the system on sequences recorded in outdoor scenarios." @default.
• W1973557579 created "2016-06-24" @default.
• W1973557579 creator A5007937949 @default.
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• W1973557579 date "2014-12-01" @default.
• W1973557579 modified "2023-09-26" @default.
• W1973557579 title "Real‐time text tracking in natural scenes" @default.
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• W1973557579 doi "https://doi.org/10.1049/iet-cvi.2013.0217" @default.
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