This paper proposes an interactive 3D animation system specifically aiming efficient control of human motion. However there are various commercial products for creating movies and game contents, those are still difficult to deal with for non-professional users. To ease the creation process and encourage to utilize 3D animation for the general users, e.g., in the field of such as education, medicine and so on, we propose a system using Kinect. The data of skeleton models of human motion estimated by Kinect is processed to generate Motion Graph and finally restructure the data automatically for 3D character models. We also propose an efficient 3D animation viewing system based on touch interface for tablet device, which enables intuitive control of multiple motions of the human activity. To evaluate the effectiveness of the method, we implemented a prototype system and created several 3D animations.

Recently importance of tablet devices with touch interface increases significantly, because they attract not only mobile phone users, but also people of all generations including small kids to elderly people. One key technology on those devices is 3D graphics; some of them exceed the ability of desktop PCs. Although currently 3D graphics are only used for game applications, it also has a great potential for other purposes. For example, an interactive 3D animation system for tablet devices has been developed recently and attracts many people. With the system, multiple 3D animations are played depending on view direction and user's gesture input. However, the system still has two critical issues: the first one is a complicated process for data creation, and the other is a conflict on several gestures overlapped at the same position. In the paper, the first issue is solved by using a realtime range sensor and the second one is solved by considering the relationship between the 3D object and the input 2D gesture. The effectiveness of the system was proved by making the real system and creating and manipulating the actual 3D animations.

This paper proposes an interpretation system for recognizing human motion behaviors and constructing the behavior rules called Behavior Grammar. The system recognizes human motion behaviors based on the gestures, locations, directions, and distances by using a distributed omnidirectional vision system (DOVS). The DOVS consisting of multiple omnidirectional cameras is a prototype of a perceptual information infrastructure for monitoring and recognizing the real world. The sequences of interpreted behaviors are represented as a behavior graph to extract behavior rules. This paper shows how the system realizes robust and real-time visual recognition based on View and Motion based Aspect Models (VAMBAM) and the resultant behavior graph.