Presentations

Violin is one of the most beautiful but also one of the most difficult musical instruments for a beginner. This paper presents an on-going work about a new augmented reality system for training how to play violin. We propose to help the players by virtually guiding the movement of the bow and the correct position of their fingers for pressing the strings. Our system also recognizes the musical note played and the correctness of its pitch. The main benefit of our system is that it does not require any specific marker since our real-time solu-tion is based on a depth camera.

Violin is one of the most beautiful but also one of the most difficult musical instruments for a beginner. This paper presents an on-going work about a new augmented reality system for training how to play violin. We propose to help the players by virtually guiding the movement of the bow and the correct position of their fingers for pressing the strings. Our system also recognizes the musical note played and the correctness of its pitch. The main benefit of our system is that it does not require any specific marker since our real-time solu-tion is based on a depth camera.

In this paper, we explore a visualization method using aug- mented maps for urban prediction. Our implementation allows users to determine the location for prediction in a paper map. As an application example, we examine an area before and af- ter new train station is built. We use the difference between two maps for simulating the changes or predicting the impact if a new train station is built on a location in a paper map. In off-line phase, we gather knowledge data from several reference loca- tions by comparing two aerial maps (before and after the train station is built). We then analyze the difference of green spaces between those two maps using color extraction. We observe that the green space around the new train station mostly decreases due to the area development. This information is then stored for prediction reference. In on-line phase, we use a monocular setup that consists of one camera and a monitor display. A paper map is captured using a web camera and tracked using its geometri- cal features. These features can be provided using the available data from Geographical Information Systems (GIS) or automat- ically extracted from the texture. The map is then matched with the reference map in database. When the map is matched, we can overlay the simulation on how the green space will change due to the existence of new train stations on a new location inputted by the user.