Automated Classifier Development Process for Recognizing Book Pages from Video Frames - Publication - Bridge of Knowledge

Your account

login

Search

Automated Classifier Development Process for Recognizing Book Pages from Video Frames

Abstract

One of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier should be suitable for real-time utilization on mobile devices, where camera can be exposed to highly diverse conditions and computing resources are limited. In this paper we address this problem by proposing an automated classifier development process that allows training classification models that run real-time, with high usability, on low-end mobile devices and achieve average accuracy of 88.95% on our in-house developed test set consisting of over 20 000 frames from real videos of 5 books for children. At the same time, deployment tests reveal that the classifier development process time is reduced approximately 16-fold.

Citations

  • 1

    CrossRef

  • 0

    Web of Science

  • 1

    Scopus

Authors (7)

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Published in:
Communications in Computer and Information Science no. 1260, pages 169 - 179,
ISSN: 1865-0929
Title of issue:
ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium strony 169 - 179
Language:
English
Publication year:
2020
Bibliographic description:
Brzeski A., Cychnerski J., Draszawka K., Dziubich K., Dziubich T., Korłub W., Rościszewski P.: Automated Classifier Development Process for Recognizing Book Pages from Video Frames// ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium/ : , 2020, s.169-179
DOI:
Digital Object Identifier (open in new tab) 10.1007/978-3-030-55814-7_14
Verified by:
Gdańsk University of Technology

seen 173 times

Recommended for you

Speech Analytics Based on Machine Learning

2019

Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions

2018

From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition

2017

Data augmentation for improving deep learning in image classification problem

2018
Meta Tags