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Application of dynamic saliency maps to the video stream recognition systems with image quality assessment
Author(s): Timofey S. Chernov; Sergey A. Ilyuhin; Vladimir V. Arlazarov
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Paper Abstract

In this paper we propose an original approach to optical video stream recognition system design, introducing new modules for image quality assessment, image quality correction and feedback. The main novelty of the proposed approach lays in combining image quality assessment results with the global dynamic object saliency maps which indicate the importance or the informative value of the corresponding image regions. The approach is applied to the identity documents video stream recognition system, where saliency maps are initially provided by document templates and are dynamically changing over time – for example, according to per-field stopping rules. Experiments demonstrated an increase of such essential recognition systems characteristics as accuracy, reliability and performance.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410T (15 March 2019); doi: 10.1117/12.2522768
Show Author Affiliations
Timofey S. Chernov, Federal Research Ctr. (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Sergey A. Ilyuhin, National Univ. of Science and Technology (Russian Federation)
Vladimir V. Arlazarov, Federal Research Ctr. (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Moscow Institute of Physics and Technology (Russian Federation)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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