An approach to road scene text recognition with per-frame accumulation and dynamic stopping decision

Konstantin Bulatov; Nadezhda Fedotova; Vladimir V. Arlazarov

doi:10.1117/12.2586912

4 January 2021 An approach to road scene text recognition with per-frame accumulation and dynamic stopping decision

Konstantin Bulatov, Nadezhda Fedotova, Vladimir V. Arlazarov

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 116051S (2021) https://doi.org/10.1117/12.2586912
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

Camera-based road scene analysis is an important task for building driving assistance systems and autonomous vehicles. An crucial component of road scene analysis is detection, tracking, and recognition of text object. In this paper, we consider the recognition of road scene text objects in sequences of video frames, and propose an approach to per-frame recognition results accumulation with a dynamic stopping decision. Experimental evaluation on an open dataset RoadText-1K showed that the proposed approach allows to achieve mean lower recognition error for the same mean number of processed frames, and significantly reduce the number of text objects which have to be recognized in each frame, thus relieving the load on the computational unit.

Citation Download Citation

Konstantin Bulatov, Nadezhda Fedotova, and Vladimir V. Arlazarov "An approach to road scene text recognition with per-frame accumulation and dynamic stopping decision", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 116051S (4 January 2021); https://doi.org/10.1117/12.2586912

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