This work examines the development of a unified motion tracking and gesture recognition system that functions through worn inertial sensors. The system is comprised of a total of ten wireless sensors and uses their quaternion output to map the player's motions to an onscreen character in real-time. To demonstrate the capabilities of the system, a simple virtual reality game was created. A hierarchical skeletal model was implemented that allows players to navigate the virtual world without the need of a handheld controller. In addition to motion tracking, the system was also tested for its potential for gesture recognition. A sensor on the right forearm was used to test six different gestures, each with 500 training samples. Despite the widespread use of Hidden Markov Models for recognition, our modified Markov Chain algorithm obtained higher average accuracies at 95%, as well as faster computation times. This makes it an ideal candidate for use in real time applications. Combining motion tracking and dynamic gesture recognition into a single unified system is unique in the literature and comes at a time when virtual reality and wearable computing are emerging in the marketplace.iii

This work presents the development and implementation of a unified multi-sensor human motion capture and gesture recognition system that can distinguish between and classify six different gestures. Data was collected from eleven participants using a subset of five wireless motion sensors (inertial measurement units) attached to their arms and upper body from a complete motion capture system. We compare Support Vector Machines and Artificial Neural Networks on the same dataset under two different scenarios and evaluate the results. Our study indicates that near perfect classification accuracies are achievable for small gestures and that the speed of classification is sufficient to allow interactivity. However, such accuracies are more difficult to obtain when a participant does not participate in training, indicating that more work needs to be done in this area to create a system that can be used by the general population.

Abstract-This work presents the development of a full body sensor-based motion tracking system that functions through wearable inertial sensors. The system is comprised of a total of ten wearable sensors and maps the player's motions to an onscreen character in real-time. A hierarchical skeletal model was implemented that allows players to navigate and interact with the virtual world without the need of a hand-held controller. To demonstrate the capabilities of the system, a simple virtual reality game was created. As a wearable system, the ability for the users to engage in activities while not being tied to a camera system, or being forced indoors presents a significant opportunity for mobile entertainment, augmented reality and interactive systems that use the body as a significant form of input. This paper outlines the key developments necessary to implement such a system.

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