Dual sensor filtering for robust tracking of head-mounted displays

Nicholas T. Swafford, Bastiaan J. Boom, Kartic Subr, D. Sinclair, Darren Cosker, Kenny Mitchell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.

Original languageEnglish
Title of host publicationProceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST 2014
Place of PublicationNew York, U. S. A.
PublisherAssociation for Computing Machinery
Pages221-222
Number of pages2
ISBN (Print)9781450332538
DOIs
Publication statusPublished - 2014
Event20th ACM Symposium on Virtual Reality Software and Technology, VRST 2014 - Edinburgh, UK United Kingdom
Duration: 11 Nov 201413 Nov 2014

Conference

Conference20th ACM Symposium on Virtual Reality Software and Technology, VRST 2014
CountryUK United Kingdom
CityEdinburgh
Period11/11/1413/11/14

Keywords

  • Fast feature tracking
  • Head-mounted display

ASJC Scopus subject areas

  • Software

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