Short-Term Trajectory Prediction for Full-Immersive Multiuser Virtual Reality with Redirected Walking

by   Filip Lemic, et al.

Full-immersive multiuser Virtual Reality (VR) envisions supporting unconstrained mobility of the users in the virtual worlds, while at the same time constraining their physical movements inside VR setups through redirected walking. For enabling delivery of high data rate video content in real-time, the supporting wireless networks will leverage highly directional communication links that will "track" the users for maintaining the Line-of-Sight (LoS) connectivity. Recurrent Neural Networks (RNNs) and in particular Long Short-Term Memory (LSTM) networks have historically presented themselves as a suitable candidate for near-term movement trajectory prediction for natural human mobility, and have also recently been shown as applicable in predicting VR users' mobility under the constraints of redirected walking. In this work, we extend these initial findings by showing that Gated Recurrent Unit (GRU) networks, another candidate from the RNN family, generally outperform the traditionally utilized LSTMs. Second, we show that context from a virtual world can enhance the accuracy of the prediction if used as an additional input feature in comparison to the more traditional utilization of solely the historical physical movements of the VR users. Finally, we show that the prediction system trained on a static number of coexisting VR users be scaled to a multi-user system without significant accuracy degradation.


page 1

page 6

page 7


Predictive Context-Awareness for Full-Immersive Multiuser Virtual Reality with Redirected Walking

The advancement of Virtual Reality (VR) technology is focused on improvi...

Comparison of Data Representations and Machine Learning Architectures for User Identification on Arbitrary Motion Sequences

Reliable and robust user identification and authentication are important...

Vibrotactile Feedback to Make Real Walking in Virtual Reality More Accessible

This research aims to examine the effects of various vibrotactile feedba...

Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks

In this paper, the problem of enhancing the virtual reality (VR) experie...

The Dark Side of Perceptual Manipulations in Virtual Reality

"Virtual-Physical Perceptual Manipulations" (VPPMs) such as redirected w...

On VR Spatial Query for Dual Entangled Worlds

With the rapid advent of Virtual Reality (VR) technology and virtual tou...

Predictive Scheduling for Virtual Reality

A significant challenge for future virtual reality (VR) applications is ...

Please sign up or login with your details

Forgot password? Click here to reset