NDLI: An empirical study into the robustness of split covariance addition (SCA) for human motion tracking

Content Provider	IEEE Xplore Digital Library
Author	Julier, S.J. La Viola Jr., J.J.
Copyright Year	2004
Description	Author affiliation: Naval Res. Lab., Washington, DC, USA (Julier, S.J.)
Abstract	Accurate human body tracking is extremely important for many virtual and augmented reality systems. However, tracking human motion is extremely difficult. Some of the difficulties arise from the fact that accurate process models of human motion are difficult to derive. Approximate models can have substantial time-correlated process noise terms. We examine the effectiveness of using the split covariance addition (SCA) algorithm as part of a human head orientation estimation system. We perform a series of empirical experiments to compare the performance of several implementations of SCA with an extended Kalman filter (EKF). The results suggest that the benefits of SCA are mixed. It leads to filters, which are slightly more robust and have slightly more accurate angular velocity estimates than the EKF. However, the absolute orientation estimate is slightly worse than the EKF.
Sponsorship	American Automatic Control Council IFAC
Starting Page	2190
Ending Page	2195
File Size	434143
Page Count	6
File Format	PDF
ISBN	0780383354
ISSN	07431619
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-06-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Robustness Humans Filters Tracking Angular velocity Augmented reality Biological system modeling Delay Degradation Turning
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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