Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes
| Autor: | Jongweon Kim, Xun Jin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
feature matching
rectilinear projection keypoint shapes 02 engineering and technology artwork identification lcsh:Technology Image (mathematics) 360-degree panoramic image lcsh:Chemistry Polyhedron Projection (mathematics) Position (vector) 0202 electrical engineering electronic engineering information engineering General Materials Science Computer vision Degree (angle) Instrumentation lcsh:QH301-705.5 Mathematics Fluid Flow and Transfer Processes business.industry lcsh:T Process Chemistry and Technology General Engineering 020207 software engineering lcsh:QC1-999 Computer Science Applications Identification (information) lcsh:Biology (General) lcsh:QD1-999 Feature (computer vision) lcsh:TA1-2040 020201 artificial intelligence & image processing Development (differential geometry) Artificial intelligence business lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
| Zdroj: | Applied Sciences, Vol 7, Iss 5, p 528 (2017) Applied Sciences; Volume 7; Issue 5; Pages: 528 |
| ISSN: | 2076-3417 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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