Web based Chinese Calligraphy Learning with 3-D Visualization Method

Wu, Yingfei; Zhuang, Yueting; Pan, Yunhe; Wu, Jiangqin

doi:10.1109/icme.2006.262642

Cited by 14 publications

(9 citation statements)

References 3 publications

(1 reference statement)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At last, a numeric grading method for judging the visually aesthetic quality was applied to make the character generated from [4] more beautiful [5]. Wu et al [6] extracted stroke's thickness and stroke's order from an offline Chinese calligraphy writing through stroke analysis and structure analysis, and then implemented a 3D visualization method to animate the characters writing process. Zhang and Zhuang [7] presented a visual verification model for historical Chinese calligraphy works by learning features that characterize an individual author's writing style.…”

Section: Related Workmentioning

confidence: 99%

Latent Style Model: Discovering writing styles for calligraphy works

Zhuang¹,

Lü²,

Wu³

2009

Journal of Visual Communication and Image Representation

Self Cite

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

Latent Style Model: Discovering writing styles for calligraphy works

Zhuang¹,

Lü²,

Wu³

2009

Journal of Visual Communication and Image Representation

Self Cite

View full text Add to dashboard Cite

“…Calligraphy has been a popular research topic recently, including calligraphy processing and analysis [8][9][10], calligraphy retrieval [11,12], visualization [13], calligraphy automatic generation or synthesis [14][15][16], calligraphy grading [17,18] and verification [19]. However, they did not focus on the style of the calligraphy that can be used to organize the calligraphy works and make users access or navigate the calligraphy collection in the style-guided manner.…”

Section: Related Workmentioning

confidence: 99%

Discovering calligraphy style relationships by Supervised Learning Weighted Random Walk Model

Lü

Zhuang

2009

Multimedia Systems

Self Cite

View full text Add to dashboard Cite

Chinese calligraphy is an important part of Chinese traditional culture. More and more calligraphy works are digitized, preserved and exhibited in digital libraries. Users may want to appreciate the style-similar works simultaneously. However, currently available services such as metadata-based browsing and searching can not satisfy such kind of requirement. To allow users to appreciate the style-similar works conveniently, we propose a Supervised Learning Weighted Random Walk Model to discover calligraphy style relationships. In the model, we consider the heterogeneity of both edges and nodes, and then use some preference pairs to learn the weights of different types of edges in the graph. After the weight learning, the style relationships can be discovered by random walk on the heterogeneous graphs. In order to solve the out-of-graph node problem, we pre-compute the personalized vector for each character or visual word, then utilize the Linearity Theory for vector addition to approximate the relationships between the new node and other nodes in graph. Then we demonstrate several applications which prove the effectiveness and efficiency of our proposed model and a user study for benefit verification. Finally, we explore some strategies to enhance the performance with the explicit or implicit user interaction including feedback, clickthrough data tracking.

show abstract

“…Users can read calligraphy books, view calligraphy works and retrieve calligraphy characters with this system. What's more, a simple demo of calligraphy writing simulation [3] is also included in the system. Some other key technologies were proposed on computer calligraphy in the last ten years, such as calligraphy retrieval [4] [5], calligraphy character synthesis [6] [7], calligraphy tablet generation [6], calligraphy character rendering [8], 3D writing process simulation [9], etc.…”

Section: Introductionmentioning

confidence: 99%

“…Wu, et cl [3] presented a simple simulator for calligraphy writing, a solid pen was used to show the stroke order of writing a specific calligraphy character. It was integrated in the first version of calligraphy system [2].…”

Section: Introductionmentioning

confidence: 99%

Chinese calligraphy system in CADAL

et al. 2011

Proceedings of 2011 International Conference on Electronic &Amp; Mechanical Engineering and Information Technology

View full text Add to dashboard Cite

In this paper, a novel Chinese calligraphy system is presented and implemented. It is designed as a new version of the calligraphy system in CADAL, and will be online in several months instead of the current version developed some years ago.In this system, users can browse and retrieve the calligraphy books, calligraphy works and calligraphy characters, user can generate a calligraphy tablet, a user can write one or more characters with common-used input devices and render them with the strokes of a specific calligrapher and a user can view the writing process of some calligraphy characters.Many latest technologies are integrated in the proposed system. The key technologies are shape based calligraphy character retrieval, style-consistent calligraphy character synthesis and calligraphy tablet generation, calligraphy character rendering, and calligraphy character writing process simulation.The system is well designed and all the subsystems work well in our experiments.

show abstract

Web based Chinese Calligraphy Learning with 3-D Visualization Method

Cited by 14 publications

References 3 publications

Latent Style Model: Discovering writing styles for calligraphy works

Latent Style Model: Discovering writing styles for calligraphy works

Discovering calligraphy style relationships by Supervised Learning Weighted Random Walk Model

Chinese calligraphy system in CADAL

Contact Info

Product

Resources

About