Real-time tracking for virtual environments using scaat kalman filtering and unsynchronised cameras

This paper presents a real-time outside-in camera-based tracking system for wireless 3D pose tracking of a user’s head and hand in a virtual environment. The system uses four unsynchronised cameras as sensors and passive retroreflective markers arranged in rigid bodies as targets. In order to achieve high update rates and to cope with the unsynchronised data a single-constraint-at-a-time (SCAAT) Extended Kalman Filtering approach is used that recursively integrates measurements as soon as they are available one-at-a-time. Tests show that this approach is more robust to occlusions and provides less noisy pose estimates with a higher update rate than a conventional stereo triangulation approach.