Kinematic Evaluation of Virtual Walking Trajectories

2017 IEEE Symposium on 3D User Interfaces (3DUI)

2017

Redirected walking with advanced planners such as MPCRed or FORCE requires both knowledge about the virtual environmentmostly in the form of a skeleton graph representing the virtual environment -and a robust prediction of the user's actions. This paper presents methods for both parts and evaluates them with a number of test cases.Since frame rate is crucial for a virtual reality application, the computationally heavy extraction and preprocessing of the skeleton graph is done offline while only parts directly linked to the user's behavior such as the prediction are done online. The prediction is done using a target-based long-term prediction and the targets are determined automatically and combined with targets predefined by the designer of the virtual environment.The methods presented here provide a graph that is well suited for planning redirection and allows prediction techniques previously only demonstrated in studies to be applied to large scale virtual environments.

Section: Discussionmentioning

confidence: 95%

“…The user position was Figure 21: Mesh C3 with visibility (red) and estimated locomotion paths for four waypoint targets. The possible user paths that were generated using Cirio et al's path model [3].…”

Section: Run-timesmentioning

confidence: 99%

Optimized graph extraction and locomotion prediction for redirected walking

2017 IEEE Symposium on 3D User Interfaces (3DUI)

2017

“…Cirio et al [4] observed that the angle α between the target's orientation and the line connecting the target and the user decreases linearly with a user's distance to a target I . Moreover, they observed that a users walking velocity is inversely proportional to his turning speed.…”

Section: Cirio Et Almentioning

confidence: 99%

Where are you going? Using human locomotion models for target estimation

2016

Vis Comput

To explore virtual environments that are larger than the available physical tracking space by real walking, it is necessary to use so-called redirected walking. Redirection techniques allow the user to explore an unlimited virtual environment in a limited tracking space by introducing a small mismatch between a user's real and virtual movement, thus preventing the user from colliding with the physical walls of the tracking space. Steering algorithms are used to select the most suitable redirection technique at any given time, depending on the geometry of the real and virtual environment. Together with prediction of a user's future walking path, these algorithms select the best redirection strategy by an optimal control scheme.In this paper, a new approach for the prediction of a person's locomotion target is presented. We use various models of human locomotion together with a set of possible targets to create a set of expected paths. These paths are then compared to the real path the user already traveled in order to calculate the probability of a certain target being the one the user is heading for. A new approach for comparing paths with each other is introduced and is compared to three others. For describing the human's path to a given target, four different models are used and compared. In order to gather data for the comparison of the models against the real path,

“…The model by Cirio et al [16] is based on their observation that the distance from user to the target I decreases linearly with the angle α between the target's orientation and the line connecting the target and the user, and the velocity is inversely proportional to the turning speed. Thus, they propose equation (1).…”

Section: ) Cirio Et Almentioning

confidence: 99%

Using Locomotion Models for Estimating Walking Targets in Immersive Virtual Environments

2015 International Conference on Cyberworlds (CW)

2015

Abstract-Redirected Walking allows a person to explore unlimited virtual environments in a limited physical tracking space. To prevent the user from colliding with the physical boundaries of the tracking space, so-called redirection techniques are used. These techniques introduce a subtle mismatch between the user's real and virtual movement and therefore keep him inside the tracking space while at the same time they allow him to explore an unlimited virtual environment. In most cases, there is more than one redirection technique available, and steering algorithms are used to select the best one at any given time. These algorithms use an optimal control scheme to select the optimal redirection action based on a prediction of the user's future path.In this paper, we present a novel approach for predicting a person's locomotion target. Using a set of known possible targets and models of human locomotion, this approach creates a set of expected paths and compares them to the path already traveled by the user in order to estimate the probability of the user heading for a certain target. We present a new approach for comparing two paths and evaluate its performance against three other approaches. We also compare four different ways of modeling a human's path to a target. To gather data for the comparison, a user study is conducted and the prediction performance of the different proposed approaches is discussed.