Motion-based perceptual user interface
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Combining inertial and visual sensing for human action recognition in tennis
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Automatic learning of gesture recognition model using SOM and SVM
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Responsive action generation by physically-based motion retrieval and adaptation
MIG'10 Proceedings of the Third international conference on Motion in games
Generalized Model-Based Human Motion Recognition with Body Partition Index Maps
Computer Graphics Forum
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Live performance is an intuitive way to naturally draft the desired motion in the choreographer's mind. In this paper we present a novel approach to choreographing motions by live performance captured with degree of freedom (3-DOF) accelerometers. The process begins by placing the accelerometers on the user's limbs according to the pre-specified positions. The computer then recognizes the performed actions using Hidden Markov Model (HMM), which is pre-trained by the acceleration data samples automatically generated from a pre-segmented motion capture database. At last, the captured actions are further synthesized with motion retiming and exaggeration based on the acceleration signals from the accelerometers. This method can intuitively rapid-prototype the choreographed motions for pre-production of animation, the avatar control in virtual reality and game-like scenarios, etc. The experimental results show that it can effectively recognize actions with spatial-time variance, and is easy-to-use especially for a novice with little experience. Copyright © 2009 John Wiley & Sons, Ltd. In this paper, we present a novel approach to creating and choreographing character animation using low-cost accelerometers based on the performer's movements. The goal of our research is to provide untrained users with an accelerometer-based interface for interactively choreographing complex human motions. It captures the movements of the performer with accelerometers, recognizes and interprets these movements based on a mocap database, and determines the motion data required to reproduce the desired movement of the performance.