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postgraduate thesis: Autocomplete hand-drawn sketches and animations
Title | Autocomplete hand-drawn sketches and animations |
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Authors | |
Issue Date | 2017 |
Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
Citation | Xing, J. [邢骏]. (2017). Autocomplete hand-drawn sketches and animations. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
Abstract | Repetition is an integral part of nature as manifested in common phenomena such as surface patterns (e.g. walls, fabrics, floors), geometry structures (e.g. stacks, pebbles, branches), dynamic motions (e.g. fluid turbulence, walking cycles, crowd movement) and human activities (e.g. drawing, gesturing, modelling). Repetition has been an important subject of study for many engineering and scientific disciplines, due to its ubiquity. The main challenge is to design methods that are general and effective, and interfaces that are simple and easy to use for diverse phenomena and application domains. This thesis presents three novel interactive systems for analyzing and synthesizing sketch and animation repetitions.
Firstly, we present an interactive digital painting system to autocomplete tedious repetitions, such as hatches and stipples, while preserving nuanced variations and maintaining natural flows. Different from previous works that focus on the static and final strokes, our system analyzes the dynamic and intermediate drawing workflow, which enables our system to understand how the strokes are drawn in the past so as to provide high-quality context-aware suggestions. Users can draw with our system as usual, while our system automatically provides and updates the suggestions online without requiring any gestures. Users can ignore or accept these suggestions similar to the auto-complete functions in common programming IDE systems, thus maintain full control.
Then, we extend the painting system to design an interactive hand-drawn animation system, which allows users to draw tedious animation frames more easily and in a better quality while preserving manual drawing practices. In particular, we extend the workflow analysis to capture both global contexts (e.g., object contours) and local details (e.g., individual strokes), so it can handle high-level structures such as complex objects in animations. We also upgrade the auto-complete design to not only predict what to draw next, but also beautify existing drawings, which is useful to help users maintain a consistent temporal flow across multiple frames.
Finally, we propose a new animation framework and interactive system that enables artists to design stylized elemental dynamics by sketching the underlying forces. Dynamic special effect, such as waves, fire, smoke and hair, are an important aspect of animation, but are very challenging to produce, as manually sketching key-frames requires significant effort and artistic expertise while physical simulation tools lack sufficient expressiveness and user control. In this system, we provide the energy brush tools for designing these elemental dynamics for animated illustrations. Users draw with coarse-scale energy brushes which serve as control gestures to drive detailed flow particles which represent local velocity fields. These fields can convey both realistic and artistic effects based on user specification. This painting metaphor for creating elemental dynamics simplifies the process, providing artistic control, and preserves the fluidity of sketching. |
Degree | Doctor of Philosophy |
Subject | Computer animation Computer drawing Drawing - Computer |
Dept/Program | Computer Science |
Persistent Identifier | http://hdl.handle.net/10722/241410 |
HKU Library Item ID | b5864187 |
DC Field | Value | Language |
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dc.contributor.author | Xing, Jun | - |
dc.contributor.author | 邢骏 | - |
dc.date.accessioned | 2017-06-13T02:07:47Z | - |
dc.date.available | 2017-06-13T02:07:47Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Xing, J. [邢骏]. (2017). Autocomplete hand-drawn sketches and animations. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
dc.identifier.uri | http://hdl.handle.net/10722/241410 | - |
dc.description.abstract | Repetition is an integral part of nature as manifested in common phenomena such as surface patterns (e.g. walls, fabrics, floors), geometry structures (e.g. stacks, pebbles, branches), dynamic motions (e.g. fluid turbulence, walking cycles, crowd movement) and human activities (e.g. drawing, gesturing, modelling). Repetition has been an important subject of study for many engineering and scientific disciplines, due to its ubiquity. The main challenge is to design methods that are general and effective, and interfaces that are simple and easy to use for diverse phenomena and application domains. This thesis presents three novel interactive systems for analyzing and synthesizing sketch and animation repetitions. Firstly, we present an interactive digital painting system to autocomplete tedious repetitions, such as hatches and stipples, while preserving nuanced variations and maintaining natural flows. Different from previous works that focus on the static and final strokes, our system analyzes the dynamic and intermediate drawing workflow, which enables our system to understand how the strokes are drawn in the past so as to provide high-quality context-aware suggestions. Users can draw with our system as usual, while our system automatically provides and updates the suggestions online without requiring any gestures. Users can ignore or accept these suggestions similar to the auto-complete functions in common programming IDE systems, thus maintain full control. Then, we extend the painting system to design an interactive hand-drawn animation system, which allows users to draw tedious animation frames more easily and in a better quality while preserving manual drawing practices. In particular, we extend the workflow analysis to capture both global contexts (e.g., object contours) and local details (e.g., individual strokes), so it can handle high-level structures such as complex objects in animations. We also upgrade the auto-complete design to not only predict what to draw next, but also beautify existing drawings, which is useful to help users maintain a consistent temporal flow across multiple frames. Finally, we propose a new animation framework and interactive system that enables artists to design stylized elemental dynamics by sketching the underlying forces. Dynamic special effect, such as waves, fire, smoke and hair, are an important aspect of animation, but are very challenging to produce, as manually sketching key-frames requires significant effort and artistic expertise while physical simulation tools lack sufficient expressiveness and user control. In this system, we provide the energy brush tools for designing these elemental dynamics for animated illustrations. Users draw with coarse-scale energy brushes which serve as control gestures to drive detailed flow particles which represent local velocity fields. These fields can convey both realistic and artistic effects based on user specification. This painting metaphor for creating elemental dynamics simplifies the process, providing artistic control, and preserves the fluidity of sketching. | - |
dc.language | eng | - |
dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject.lcsh | Computer animation | - |
dc.subject.lcsh | Computer drawing | - |
dc.subject.lcsh | Drawing - Computer | - |
dc.title | Autocomplete hand-drawn sketches and animations | - |
dc.type | PG_Thesis | - |
dc.identifier.hkul | b5864187 | - |
dc.description.thesisname | Doctor of Philosophy | - |
dc.description.thesislevel | Doctoral | - |
dc.description.thesisdiscipline | Computer Science | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.mmsid | 991026390289703414 | - |