A 3D tracking experiment on latency and its compensation methods in virtual environments

Wu, Jiann-Rong; Ouhyoung, Ming

doi:10.1145/215585.215650

Cited by 19 publications

(13 citation statements)

References 13 publications

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“…Wu & Ouhyoung's [24] comparative evaluation of their Grey System method was carried out by fixing the prediction interval to constant values. Akatsuka and Bekey [1] evaluated their method of head-tracking latency compensation assuming a static network delay that depended on the complexity of the rendered scene.…”

Section: Proactive Latency Compensationmentioning

confidence: 99%

Variability-Aware Latency Amelioration in Distributed Environments

Tumanov

Allison

Stuerzlinger

2007

2007 IEEE Virtual Reality Conference

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Application designers of collaborative distributed Virtual Environments must account for the influence of the network connection and its detrimental effects on user performance. Based upon analysis and classification of existing latency compensation techniques, this paper introduces a novel approach to latency amelioration in the form of a two-tier predictor-estimator framework. The technique is variability-aware due to its proactive sender-side prediction of a pose a variable time into the future. The prediction interval required is estimated based on current and past network delay characteristics. This latency estimate is subsequently used by a Kalman Filter-based predictor to replace the measurement event with a predicted pose that matches the event's arrival time at the receiving workstation. The compensation technique was evaluated in a simulation through an offline playback of real head motion data and network delay traces collected under a variety of real network conditions. The experimental results indicate that the variability-aware approach significantly outperforms a state-of-the-art one, which assumes a constant system delay.

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Section: Proactive Latency Compensationmentioning

confidence: 99%

Variability-Aware Latency Amelioration in Distributed Environments

Tumanov

Allison

Stuerzlinger

2007

2007 IEEE Virtual Reality Conference

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“…Increases in lag time between the interactive movements and the presentation of the sensory results of that movement cannot become too great, or performance will necessarily deteriorate (MacKenzie & Ware, 1993;Wu & Ouhyoung, 1995;Welch, Blackmon, Liu, Mellers, & Stark, 1996). Thus, a fine balance, trading off improvements in the presentation of feedback information and performance decrements, must be delineated in an application-and taskspecific fashion.…”

Section: Implications For Human-computer Interactionmentioning

confidence: 99%

The Role of Graphical Feedback About Self-Movement when Receiving Objects in an Augmented Environment

Mason

MacKenzie

2004

Presence: Teleoperators & Virtual Environments

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This work explored how the presence of graphical information about selfmovement affected reach-to-grasp movements in an augmented environment. Twelve subjects reached to grasp objects that were passed by a partner or rested on a table surface. Graphical feedback about self-movement was available for half the trials and was removed for the other half. Results indicated that removing visual feedback about self-movement in an object-passing task dramatically affected both the receiver's movement to grasp the object and the time to transfer the object between partners. Specifically, the receiver's deceleration time, and temporal and spatial aspects of grasp formation, showed significant effects. Results also indicated that the presence of a graphic representation of self-movement had similar effects on the kinematics of reaching to grasp a stationary object on a table as for one held by a stationary or moving partner. These results suggest that performance of goal-directed movements, whether to a stationary object on a table surface or to objects being passed by a stationary or moving partner, benefits from a crude graphical representation of the finger pads. The role of providing graphic feedback about self-movement is discussed for tasks requiring precision. Implications for the use of kinematic measures in the field of Human-Computer Interaction (HCI) are also discussed. IntroductionAs humans, we have the exquisite ability to successfully perform a tremendous number of complex actions with seeming ease. One of the ways in which these complex movements is achieved is through the use of sensory information, gathered from the environment by exteroceptors (e.g., eyes, ears). This sensory information is gathered before the initiation of the movement, for use in generating a motor plan that will direct the performance of the complex action. In addition, sensory feedback is used on-line during the production of movements to fine-tune our actions such that success can be achieved. One of the most critical organs for providing information about objects and their movement in the environment is the eye. Visual feedback is crucial for the accurate and successful performance of many motor activities in both natural and computer-generated environments.In natural environments, sources of visual information are rich, spatially and temporally accurate, and readily available. However, due to limitations in curMason and MacKenzie 507

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“…A comparison of "Grey systems" and Kalman filtering for prediction was conducted by Wu and Ouhyoung [1995]. Both techniques improved performance when lag is as high as 120 ms, but Kalman filtering provided the least "jitter".…”

Section: Related Researchmentioning

confidence: 99%

System lag tests for augmented and virtual environments

Swindells

Dill

Booth

2000

Proceedings of the 13th Annual ACM Symposium on User Interface Software and Technology - UIST '00

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We describe a simple technique for accurately calibrating the temporal lag in augmented and virtual environments within the Enhanced Virtual Hand Lab (EVHL), a collection of hardware and software to support research on goal-directed human hand motion. Lag is the sum of various delays in the data pipeline associated with sensing, processing, and displaying information from the physical world to produce an augmented or virtual world. Our main calibration technique uses a modified phonograph turntable to provide easily tracked periodic motion, reminiscent of the pendulum-based calibration technique of Liang, Shaw and Green. Measurements show a three-frame (50 ms) lag for the EVHL. A second technique, which uses a specialized analog sensor that is part of the EVHL, provides a "closed loop" calibration capable of sub-frame accuracy. Knowing the lag to sub-frame accuracy enables a predictive tracking scheme to compensate for the end-toend lag in the data pipeline. We describe both techniques and the EVHL environment in which they are used.

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A 3D tracking experiment on latency and its compensation methods in virtual environments

Cited by 19 publications

References 13 publications

Variability-Aware Latency Amelioration in Distributed Environments

Variability-Aware Latency Amelioration in Distributed Environments

The Role of Graphical Feedback About Self-Movement when Receiving Objects in an Augmented Environment

System lag tests for augmented and virtual environments

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