研究生: |
林沿榆 Rina Savista Halim |
---|---|
論文名稱: |
Chinese Painting Koi Animation with Controllable Brush Stroke using Generative Adversarial Networks Chinese Painting Koi Animation with Controllable Brush Stroke using Generative Adversarial Networks |
指導教授: |
姚智原
Chih-Yuan Yao |
口試委員: |
阮聖彰
Shanq-Jang Ruan 朱宏國 Hung-Kuo Chu |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
論文出版年: | 2019 |
畢業學年度: | 107 |
語文別: | 英文 |
論文頁數: | 64 |
中文關鍵詞: | animation 、Chinese painting 、Non-photorealistic Rendering 、Generative Adversarial Networks |
外文關鍵詞: | animation, Chinese painting, Non-photorealistic Rendering, Generative Adversarial Networks |
相關次數: | 點閱:343 下載:0 |
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The process to produce a Chinese painting animation where the artists are
required to create every frame might be time-consuming. We proposed a system to
generate a Chinese painting animation along with some user-interactions automati-
cally. The inputs for the system are 3D koi (decorative carp) and background, e.g.,
lotus and leaf models. The system creates user-interactive ripples and streamlines
caused by the swimming of the koi automatically. The system also provides a boat
scene along with the wave-line caused by the movement of the boat.
The user-interactive ripple utilizes both the mass-spring model and image space
computation for ripple simulation proposed by Zhang and Yang [1] and Navier-
Stokes equation as used by Stam [2]. For the streamline, its base shape is based on
multiple continuous ripples with contour extraction applied. Closing and blur eect
is later applied to the base shape to create the nal streamline. The wave-line of
the boat is created with the Navier-Stokes equation with added force and specic
velocity for every frame.
Another feature of the system is koi's contours stroke. There are three styles
of stroke available and four stroke-sizes provided. The stroke is generated with
Generative Adversarial Networks (GANs). The generator in this network is based
on the autoencoder model with skip-connection applied to some of its layers to keep
the underlying feature of the input image. The discriminator has two tasks which are
discriminating whether the image is real or fake and classifying the stroke-size. To
discriminator is based on PatchGAN with an added fully-connected layer to classify
the stroke-size.
The process to produce a Chinese painting animation where the artists are
required to create every frame might be time-consuming. We proposed a system to
generate a Chinese painting animation along with some user-interactions automati-
cally. The inputs for the system are 3D koi (decorative carp) and background, e.g.,
lotus and leaf models. The system creates user-interactive ripples and streamlines
caused by the swimming of the koi automatically. The system also provides a boat
scene along with the wave-line caused by the movement of the boat.
The user-interactive ripple utilizes both the mass-spring model and image space
computation for ripple simulation proposed by Zhang and Yang [1] and Navier-
Stokes equation as used by Stam [2]. For the streamline, its base shape is based on
multiple continuous ripples with contour extraction applied. Closing and blur eect
is later applied to the base shape to create the nal streamline. The wave-line of
the boat is created with the Navier-Stokes equation with added force and specic
velocity for every frame.
Another feature of the system is koi's contours stroke. There are three styles
of stroke available and four stroke-sizes provided. The stroke is generated with
Generative Adversarial Networks (GANs). The generator in this network is based
on the autoencoder model with skip-connection applied to some of its layers to keep
the underlying feature of the input image. The discriminator has two tasks which are
discriminating whether the image is real or fake and classifying the stroke-size. To
discriminator is based on PatchGAN with an added fully-connected layer to classify
the stroke-size.
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