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Viability of Viola-Jones method for the problem of image classification
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Paper Abstract

In this paper we study combination of Viola-Jones classifier with deep convolutional neural network as an approach to the problem of object detection and classification. It is well known that Viola-Jones detectors are fast and accurate in detection of vast variety of different objects. On the other hand, methods based on neural network usage demonstrate high accuracy in the problems of image classification. The main goal of this paper is to study viability of Viola-Jones classifier in problem of image classification. The first part of both algorithms is the same: we will use Viola-Jones classifier to find object bounding rectangle in the image. The second part of the algorithms is different: we will compare usage of Viola-Jones classifier with convolutional neural network-based classifier. We will provide speed and accuracy comparison between these two algorithms.

Paper Details

Date Published: 15 March 2019
PDF: 7 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410E (15 March 2019); doi: 10.1117/12.2522971
Show Author Affiliations
Alexander Sheshkus, Federal Research Ctr. (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Daniil Matalov, Smart Engines Ltd. (Russian Federation)
Moscow Institute of Physics and Technology (Russian Federation)
Vladimir V. Arlazarov, Federal Research Ctr. (Russian Federation)
Smart Engines Ltd. (Russian Federation)
Institute for Information Transmission Problems (Russian Federation)
Dmitry P. Nikolaev, Institute for Information Transmission Problems (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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