Developing a M-learning System for End-Game Strategy and Killing of Chinese Chess Using Mobile Phone AR

• Main Authors: Yu-Syuan Tsai, 蔡宇軒
• Other Authors: Lieu-Hen Chen
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/27444786467940214511

碩士 === 國立暨南國際大學 === 資訊工程學系 === 98 === Augmented Reality (AR) is an important and practical research field, which combines real and virtual images. In recent years, as AR technology improves human perspective with enhanced reality and provides better interaction, more and more research is has been devoted to this field. By combining real world scenes with virtual objects and supporting a novel User Interface of AR, the learning curves of users are greatly improved for both purposes of education and entertainment. Chinese chess (Xiangqi) has a long history. Today, Chinese chess is one of the most popular board games in the world. There are many “kifu”, strategic records and tactical patterns of games, being written from ancient times to the present. A kifu of Chinese chess records the playing process, which is very helpful for players to learn and analyze the strategies of Chinese chess at three distinct phases; the opening, middle game, and ending. In this paper, we develop a remote training system for Chinese chess using mobile phone augmented reality. By employing AR technology, we can learn from tutorials and play chess without a real chess board. A virtual board and 3D chess pieces are now visualized throughout the display of the mobile phone. We also provide multimodal user interfaces. Player can “directly” pick up and move a chess piece on the board by the screen of his mobile phone. This approach provides perhaps the most natural Human Machine Interface to play chess for users. Finally, 3D animation of the game records and related kifu is shown for users to further improve their skills. Most importantly, this system provides a “prepare killing” and “end game” tutorial, which can teach novices how to checkmate an opponent more efficiently.