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Abstract
We propose a novel method of improving algorithms recognizing traffic lights in video sequences. Our focus is on algorithms for applications which notify the driver of a light in sight. Many existing methods process images in the recording separately. Our method bases on the observation that real-life videos depict underlying continuous processes. We named our method FSA (Frame Sequence Analyzed). It is applicable for any underlying algorithm and improves it by adding an additional result post-processing step. Our experiments are based on improving a published realtime traffic light recognition algorithm. Its general description has been provided by its authors, which allowed us to create a best-effort implementation for testing. We verify the effectiveness of the FSA method on a public dataset, acquiring very good results - improving the underlying algorithm in terms of all considered error measures. In the end, conclusions and possible future improvements are discussed.
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Authors (2)
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Adam Blokus Dr inż
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- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- Proc. 25th Int. Conference on System, Signals and Image Processing strony 46 - 52
- ISSN:
- 2157-8702
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Blokus A., Krawczyk H..: Improving Traffic Light Recognition Methods using Shifting Time-Windows, W: Proc. 25th Int. Conference on System, Signals and Image Processing, 2018, ,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/iwssip.2018.8439187
- Sources of funding:
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- Project n/d
- Verified by:
- Gdańsk University of Technology
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