MOCA: A Low-Power, Low-Cost Motion Capture System Based on Integrated Accelerometers

Human-computer interaction (HCI) and virtual reality applications pose the challenge of enabling real-time interfaces for natural interaction. Gesture recognition based on body-mounted accelerometers has been proposed as a viable solution to translate patterns of movements that are associated with user commands, thus substituting point-and-click methods or other cumbersome input devices. On the other hand, cost and power constraints make the implementation of a natural and efficient interface suitable for consumer applications a critical task. Even though several gesture recognition solutions exist, their use in HCI context has been poorly characterized. For this reason, in this paper, we consider a low-cost/low-power wearable motion tracking system based on integrated accelerometers called motion capture with accelerometers (MOCA) that we evaluated for navigation in virtual spaces. Recognition is based on a geometric algorithm that enables efficient and robust detection of rotational movements. Our objective is to demonstrate that such a low-cost and a low-power implementation is suitable for HCI applications. To this purpose, we characterized the system from both a quantitative point of view and a qualitative point of view. First, we performed static and dynamic assessment of movement recognition accuracy. Second, we evaluated the effectiveness of user experience using a 3D game application as a test bed

A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste