A Recurrent Neural Network Approach to Virtual Environment Latency Reduction
نویسندگان
چکیده
We present a recurrent neural network system designed to predict future angular acceleration of the human head from current angular acceleration data. These predictions can be used to supplement head tracking in virtual environments in order to reduce latency and increase tracking accuracy, thus enhancing the user’s performance and comfort.
منابع مشابه
Navigation of a Mobile Robot Using Virtual Potential Field and Artificial Neural Network
Mobile robot navigation is one of the basic problems in robotics. In this paper, a new approach is proposed for autonomous mobile robot navigation in an unknown environment. The proposed approach is based on learning virtual parallel paths that propel the mobile robot toward the track using a multi-layer, feed-forward neural network. For training, a human operator navigates the mobile robot in ...
متن کاملDesign of a Low-Latency Router Based on Virtual Output Queuing and Bypass Channels for Wireless Network-on-Chip
Wireless network-on-chip (WiNoC) is considered as a novel approach for designing future multi-core systems. In WiNoCs, wireless routers (WRs) utilize high-bandwidth wireless links to reduce the transmission delay between the long distance nodes. When the network traffic loads increase, a large number of packets will be sent into the wired and wireless links and can...
متن کاملReconstruction of the neural network model of motor control for virtual C.elegans on the basis of actual organism information
Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...
متن کاملA Recurrent Neural Network to Identify Efficient Decision Making Units in Data Envelopment Analysis
In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...
متن کاملA Recurrent Neural Network Model for solving CCR Model in Data Envelopment Analysis
In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001