| S. Emura and S. Tachi. Multisensor integrated prediction for virtual reality. Presence: Teleoperators and Virtual Environments, 7(4):410-- 422, aug 1998. |
....Since vision sensors (cameras) nominally sample at video rates (30Hz) they are most appropriate for measuring low frequency pose variations. Rapid or abrupt camera rotations or motions can cause vision tracking failures or instabilities. Inertial sensors are widely used for motion tracking [4, 8, 10, 12, 18]. These sensors are self contained, sourceless, and can be sampled at high rates ( 1KHz) The latter characteristic makes them suitable for sensing the rapid motions that create high frequency pose variations. However, inertial sensors only measure motion rates or accelerations; their signals must ....
....for system delay and an EKF is used for data fusion. Chai et al. 8] uses an adaptive pose estimator with vision and inertial sensors for head tracking. The EKF estimator used multiple models of the expected user head motion to allow for variations in the range of expected motions. Emura et al. [10] suggests a hybrid tracking system consisting of a magnetic tracker and gyro sensor that compensates for the latency in the magnetic tracker. AR tracking in unconstrained environments, especially outdoors, is a challenge problem. In [11] Columbia s Touring Machine tracks outdoors by combining a ....
S. Emura and S. Tachi, "Multisensor Integrated Prediction for Virtual Reality", Presence, Vol 7. No 4, pp. 410-422, 1998.
No context found.
S. Emura and S. Tachi. Multisensor integrated prediction for virtual reality. Presence: Teleoperators and Virtual Environments, 7(4):410-- 422, aug 1998.
No context found.
S. Emura, and S. Tachi, "Multisensor Integrated Prediction for Virtual Reality". Presence: Teleoperators & Virtual Environments, Vol 7. no. 4, 1998, pp. 410-422.
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