Dual sensor filtering for robust tracking of head-mounted displays

PubDate: November 2014

Teams: University of Bath；Disney Research

Writers: Nicholas T. Swafford；Bastiaan J. Boom；Kartic Subr；David Sinclair；Darren Cosker；Kenny Mitchell

PDF: Dual sensor filtering for robust tracking of head-mounted displays

Abstract

We present a low-cost solution for yaw drift in head-mounted display systems that performs better than current commercial solutions and provides a wide capture area for pose tracking. Our method applies an extended Kalman filter to combine marker tracking data from an overhead camera with onboard head-mounted display accelerometer readings. To achieve low latency, we accelerate marker tracking with color blob localisation and perform this computation on the camera server, which only transmits essential pose data over WiFi for an unencumbered virtual reality system.