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Interactive landsca...
Interactive landscape–scale cloud animation using DCGAN
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- Goswami, Prashant, 1980- (författare)
- Blekinge Tekniska Högskola,Institutionen för datavetenskap,DIDA
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- Cheddad, Abbas (författare)
- Blekinge Tekniska Högskola,Institutionen för datavetenskap,DIDA
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- Junede, Fredrik (författare)
- Blekinge Tekniska Högskola,student
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- Asp, Samuel (författare)
- Blekinge Tekniska Högskola,student
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(creator_code:org_t)
- 2023-03-08
- 2023
- Engelska.
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Ingår i: Frontiers in Computer Science. - : Frontiers Media S.A.. - 2624-9898. ; 5
- Relaterad länk:
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https://doi.org/10.3...
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https://www.frontier...
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https://bth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- This article presents an interactive method for 3D cloud animation at the landscape scale by employing machine learning. To this end, we utilize deep convolutional generative adversarial network (DCGAN) on GPU for training on home-captured cloud videos and producing coherent animation frames. We limit the size of input images provided to DCGAN, thereby reducing the training time and yet producing detailed 3D animation frames. This is made possible through our preprocessing of the source videos, wherein several corrections are applied to the extracted frames to provide an adequate input training data set to DCGAN. A significant advantage of the presented cloud animation is that it does not require any underlying physics simulation. We present detailed results of our approach and verify its effectiveness using human perceptual evaluation. Our results indicate that the proposed method is capable of convincingly realistic 3D cloud animation, as perceived by the participants, without introducing too much computational overhead.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- cloud animation
- deep convolutional generative adversarial networks (DCGAN)
- multimedia (image/video/music)
- machine learning
- image processing
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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