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Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection
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Paper Abstract

This paper aims to study the problem of multi-class object detection in video stream with Viola-Jones cascades. An adaptive algorithm for selecting Viola-Jones cascade based on greedy choice strategy in solution of the N-armed bandit problem is proposed. The efficiency of the algorithm on the problem of detection and recognition of the bank card logos in the video stream is shown. The proposed algorithm can be effectively used in documents localization and identification, recognition of road scene elements, localization and tracking of the lengthy objects , and for solving other problems of rigid object detection in a heterogeneous data flows. The computational efficiency of the algorithm makes it possible to use it both on personal computers and on mobile devices based on processors with low power consumption.

Paper Details

Date Published: 13 April 2018
PDF: 8 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960D (13 April 2018); doi: 10.1117/12.2310101
Show Author Affiliations
Alexander A. Tereshin, Bournemouth Univ. (United Kingdom)
Smart Engines (Russian Federation)
Sergey A. Usilin, Smart Engines (Russian Federation)
ISA FRC CSC RAS (Russian Federation)
Vladimir V. Arlazarov, Smart Engines (Russian Federation)
ISA FRC CSC RAS (Russian Federation)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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