Head-mounted displays (HMDs) in room-scale virtual reality are usually tracked using inside-out visual SLAM algorithms. Alternatively, to track the motion of the HMD with respect to a fixed real-world reference frame, an outside-in instrumentation like a motion capture system can be adopted. However, outside-in tracking systems may temporarily lose tracking as they suffer by occlusion and blind spots. A possible solution is to adopt a hybrid approach where the inside-out tracker of the HMD is augmented with an outside-in sensing system. On the other hand, when the tracking signal of the outside-in system is recovered after a loss of tracking the transition from inside-out tracking to hybrid tracking may generate a discontinuity, i.e a sudden change of the virtual viewpoint, that can be uncomfortable for the user. Therefore, hybrid tracking solutions for HMDs require advanced sensor fusion algorithms to obtain a smooth transition. This work proposes a method for hybrid tracking of a HMD with smooth transitions based on an adaptive complementary filter. The proposed approach can be configured with several parameters that determine a trade-off between user experience and tracking error. A user study was carried out in a room-scale virtual reality environment, where users carried out two different tasks while multiple signal tracking losses of the outside-in sensor system occurred. The results show that the proposed approach improves user experience compared to a standard Extended Kalman Filter, and that tracking error is lower compared to a state-of-the-art complementary filter when configured for the same quality of user experience.

Adaptive Complementary Filter for Hybrid Inside-Out Outside-In HMD Tracking With Smooth Transitions / Monica, R.; Lodi Rizzini, D.; Aleotti, J.. - In: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS. - ISSN 1077-2626. - 31:2(2025), pp. 1598-1612. [10.1109/TVCG.2024.3464738]

Adaptive Complementary Filter for Hybrid Inside-Out Outside-In HMD Tracking With Smooth Transitions

Monica R.
;
Lodi Rizzini D.;Aleotti J.
2025-01-01

Abstract

Head-mounted displays (HMDs) in room-scale virtual reality are usually tracked using inside-out visual SLAM algorithms. Alternatively, to track the motion of the HMD with respect to a fixed real-world reference frame, an outside-in instrumentation like a motion capture system can be adopted. However, outside-in tracking systems may temporarily lose tracking as they suffer by occlusion and blind spots. A possible solution is to adopt a hybrid approach where the inside-out tracker of the HMD is augmented with an outside-in sensing system. On the other hand, when the tracking signal of the outside-in system is recovered after a loss of tracking the transition from inside-out tracking to hybrid tracking may generate a discontinuity, i.e a sudden change of the virtual viewpoint, that can be uncomfortable for the user. Therefore, hybrid tracking solutions for HMDs require advanced sensor fusion algorithms to obtain a smooth transition. This work proposes a method for hybrid tracking of a HMD with smooth transitions based on an adaptive complementary filter. The proposed approach can be configured with several parameters that determine a trade-off between user experience and tracking error. A user study was carried out in a room-scale virtual reality environment, where users carried out two different tasks while multiple signal tracking losses of the outside-in sensor system occurred. The results show that the proposed approach improves user experience compared to a standard Extended Kalman Filter, and that tracking error is lower compared to a state-of-the-art complementary filter when configured for the same quality of user experience.
2025
Adaptive Complementary Filter for Hybrid Inside-Out Outside-In HMD Tracking With Smooth Transitions / Monica, R.; Lodi Rizzini, D.; Aleotti, J.. - In: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS. - ISSN 1077-2626. - 31:2(2025), pp. 1598-1612. [10.1109/TVCG.2024.3464738]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/3015273
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