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Animated lightning bolt generation using machine learning
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-6920-9983
Blekinge Institute of Technology. student.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-4390-411X
2023 (English)In: 12th International Conference on Image Processing Theory, Tools and Applications, IPTA 2023, Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we investigate the possibility of leveraging the predictive power of machine learning to generate animated lightning bolts in the image space efficiently. To this end, we selected state-of-the-art machine learning architectures based on Generative Adversarial Network (GAN) and trained them on the commonly available videos. We demonstrate that visually convincing animations are achievable even when employing a limited dataset. The visual realism of the generated sequences of lightning bolts is assessed by conducting a user study on the participants.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023.
Keywords [en]
lightning, animation, GAN, machine learning
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:bth-25819DOI: 10.1109/IPTA59101.2023.10320085Scopus ID: 2-s2.0-85179547685ISBN: 9798350325416 (print)OAI: oai:DiVA.org:bth-25819DiVA, id: diva2:1822610
Conference
12th International Conference on Image Processing Theory, Tools and Applications, IPTA 2023, Paris, 16 October through 19 October 2023
Available from: 2023-12-27 Created: 2023-12-27 Last updated: 2025-09-30Bibliographically approved

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fulltext(3396 kB)236 downloads
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Goswami, PrashantCheddad, Abbas

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CiteExportLink to record
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