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

Alexander Sheshkus; Daniil Matalov; Vladimir V. Arlazarov; Dmitry P. Nikolaev

doi:10.1117/12.2522971

15 March 2019 Viability of Viola-Jones method for the problem of image classification

Alexander Sheshkus, Daniil Matalov, Vladimir V. Arlazarov, Dmitry P. Nikolaev

Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110410E (2019) https://doi.org/10.1117/12.2522971
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany

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.

Citation Download Citation

Alexander Sheshkus, Daniil Matalov, Vladimir V. Arlazarov, and Dmitry P. Nikolaev "Viability of Viola-Jones method for the problem of image classification", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410E (15 March 2019); https://doi.org/10.1117/12.2522971

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available