Next Article in Journal
X-ray Pump–Probe Investigation of Charge and Dissociation Dynamics in Methyl Iodine Molecule
Next Article in Special Issue
Stereoscopic Image Super-Resolution Method with View Incorporation and Convolutional Neural Networks
Previous Article in Journal
Application of Pulsed Laser-TIG Hybrid Heat Source in Root Welding of Thick Plate Titanium Alloys
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(5), 528; doi:10.3390/app7050528

Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes

1
Department of Copyright Protection, Sangmyung University, Seoul 03016, Korea
2
Department of Electronics Engineering, Sangmyung University, Seoul 03016, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Martin Richardson
Received: 24 February 2017 / Revised: 29 April 2017 / Accepted: 17 May 2017 / Published: 19 May 2017
(This article belongs to the Special Issue Holography and 3D Imaging: Tomorrows Ultimate Experience)

Abstract

With the increased development of 360-degree production technologies, artwork has recently been photographed without authorization. To prevent this infringement, we propose an artwork identification methodology for 360-degree images. We transform the 360-degree image into a three-dimensional sphere and wrap it with a polyhedron. On the sphere, several points are located on the polyhedron to determine the width, height, and direction of the rectilinear projection. The 360-degree image is divided and transformed into several rectilinear projected images to reduce the adverse effects from the distorted panoramic image. We also propose a method for improving the identification precision of artwork located at a highly distorted position using the difference of keypoint shapes. After applying the proposed methods, identification precision is increased by 45% for artwork that is displayed on a 79-inch monitor in a seriously distorted position with features that were generated by scale-invariant feature transformations. View Full-Text
Keywords: artwork identification; 360-degree panoramic image; rectilinear projection; feature matching; keypoint shapes artwork identification; 360-degree panoramic image; rectilinear projection; feature matching; keypoint shapes
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Jin, X.; Kim, J. Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes. Appl. Sci. 2017, 7, 528.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top