Automatic Field-of-View Expansion using Deep Features and Image Stitching
| Autor: | Bagus Satriyawibowo, Rini Wongso, Juan Leegard Ranteallo Sampetoding, Williem, Ferdinand Ariandy Luwinda |
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| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry 3D reconstruction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering Field of view 02 engineering and technology Computer graphics Image stitching 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Computer vision Artificial intelligence business General Environmental Science |
| Zdroj: | Procedia Computer Science. 135:657-662 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2018.08.230 |
| Popis: | Automatic photo enhancement, such field-of-view expansion, has become a challenging problem in computer graphics community. Due to the hardware limitation, image acquisition might get distracted by small field-of-view. Photo enhancement using internet photo collections has gained good performance in the past few years. However, it depends on the quality of 3D reconstruction. In this paper, we perform an automatic personal photo enhancement using the photo collection without any 3D reconstruction step. 2D global descriptor is used using NetVLAD deep architecture. Then, image stitching is applied for each similar candidate image. Experiment results show that the propose framework has promising results which could lead to further research. |
| Databáze: | OpenAIRE |
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