VIS-Tracker: a wearable vision-inertial self-tracker

Foxlin, Eric; Naimark, Leonid

doi:10.1109/vr.2003.1191139

Cited by 109 publications

(55 citation statements)

References 6 publications

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“…The participants started the user study in the center of the maze's lower end. Paper markers for the the Intersense IS-1200 tracking system [24] were attached to the ceiling of the room, in which the T-maze was installed. The sensor of the IS-1200 tracking system (inside-out tracking system) can be easily attached to an HMD.…”

Section: Methodsmentioning

confidence: 99%

Using Head Tracking Data for Robust Short Term Path Prediction of Human Locomotion

Nescher

Künz

2013

Lecture Notes in Computer Science

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Modern interactive environments like virtual reality simulators or augmented reality systems often require reliable information about a user's future intention in order to increase their immersion and usefulness. For many of such systems, where human locomotion is an essential way of interaction, knowing a user's future walking direction provides relevant information.This paper explains how head tracking data can be used to retrieve a person's intended direction of walking. The goal is to provide a reliable and stable path prediction of human locomotion that holds for a few seconds. Using 6 degrees of freedom head tracking data, the head orientation and the head's movement direction can be derived. Within a user study it is shown that such raw tracking data provides poor prediction results mainly due to noise from gait oscillations. Hence, smoothing filters have to be applied to the data to increase the reliability and robustness of a predictor.Results of the user study show that double exponential smoothing of a person's walking direction data in combination with an initialization using the head orientation provides a reliable short term path predictor with high robustness.

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Section: Methodsmentioning

confidence: 99%

Using Head Tracking Data for Robust Short Term Path Prediction of Human Locomotion

Nescher

Künz

2013

Lecture Notes in Computer Science

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“…Hardware An Intersense IS-1200 tracking system [6] was installed in a 12.6 m × 6.2 m room (tracks 1 point with 6 degrees of freedom at 180Hz). The tracking device was attached to an Oculus Rift 1 HMD (640x800 resolution per eye, 110 degrees diagonal field of view).…”

Section: Equipmentmentioning

confidence: 99%

Planning redirection techniques for optimal free walking experience using model predictive control

Nescher

Huang

Kunz

2014

2014 IEEE Symposium on 3D User Interfaces (3DUI)

125

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Redirected Walking (RDW) is a technique that allows exploring immersive virtual environments by real walking in a small physical room. RDW employs so-called redirection techniques (RETs) to manipulate the user's real world trajectory in such a way that he remains within the boundaries of the physical room. Different RETs were suggested and evaluated in the past. In addition, steering algorithms were proposed that apply a limited set of RETs to redirect a user away from the physical room's boundaries.Within this paper, a generalized approach to planning and applying RETs is presented. It is capable of dynamically selecting suitable RETs and also controlling parameters like their strengths. The problem of steering a user in a small physical room using RETs is formulated as an optimal control problem. This allows applying an efficient probabilistic planning algorithm to maximize the free walking experience. The proposed algorithm uses a map of the virtual environment to continuously determine the optimal RET that has to be applied next.The suggested algorithm is evaluated within a user study and compared to a state-of-the-art steering algorithm. Results show that for the given virtual environment, it is able to reduce the number of collisions with the room boundaries by 41% and furthermore reduces the amount of applied redirections significantly.

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“…Koller et al [15] used an EKF with a single camera and an acceleration-level process model; You et al [23] used an additive EKF with gyro measurements; Foxlin et al [9] developed a wearable tracking device that fuses vision and IMU measurements using an EKF; and more recently, Bleser and Stricker [2] used a sensor fusion model-based tracker using a quaternion based EKF.…”

Section: Related Workmentioning

confidence: 99%

Sequential Pose Estimation Using Linearized Rotation Matrices

Drews

Kry

Forbes

et al. 2013

2013 International Conference on Computer and Robot Vision

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Abstract-We present a new formulation for pose estimation using an extended Kalman filter that takes advantage of the Lie group structure of rotations. Using the exponential map along with linearized rotations for updates and errors permits a graceful filter formulation that avoids the awkward representation of Euler angles and the required norm constraint for quaternions. We demonstrate this approach with an implementation that uses sensors commonly found in consumer tablets and mobile phones: a camera and gyroscope, which we use to estimate attitude, position, and gyroscope bias. We use gyroscope measurements for prediction, and vision-based measurements for correction. We show results and discuss the performance of our pose estimation method using ground truth data obtained via a motion capture system.

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VIS-Tracker: a wearable vision-inertial self-tracker

Cited by 109 publications

References 6 publications

Using Head Tracking Data for Robust Short Term Path Prediction of Human Locomotion

Using Head Tracking Data for Robust Short Term Path Prediction of Human Locomotion

Planning redirection techniques for optimal free walking experience using model predictive control

Sequential Pose Estimation Using Linearized Rotation Matrices

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