4,967 research outputs found
Natural User Interface for Education in Virtual Environments
Education and self-improvement are key features of human behavior. However, learning in the physical world is not always desirable or achievable. That is how simulators came to be. There are domains where purely virtual simulators can be created in contrast to physical ones. In this research we present a novel environment for learning, using a natural user interface. We, humans, are not designed to operate and manipulate objects via keyboard, mouse or a controller. The natural way of interaction and communication is achieved through our actuators (hands and feet) and our sensors (hearing, vision, touch, smell and taste). That is the reason why it makes more sense to use sensors that can track our skeletal movements, are able to estimate our pose, and interpret our gestures. After acquiring and processing the desired – natural input, a system can analyze and translate those gestures into movement signals
Activity-promoting gaming systems in exercise and rehabilitation
Commercial activity-promoting gaming systems provide a potentially attractive means to facilitate exercise and rehabilitation. The Nintendo Wii, Sony EyeToy, Dance Dance Revolution, and Xbox Kinect are examples of gaming systems that use the movement of the player to control gameplay. Activity-promoting gaming systems can be used as a tool to increase activity levels in otherwise sedentary gamers and also be an effective tool to aid rehabilitation in clinical settings. Therefore, the aim of this current work is to review the growing area of activity-promoting gaming in the context of exercise, injury, and rehabilitation
GEMINI: A Generic Multi-Modal Natural Interface Framework for Videogames
In recent years videogame companies have recognized the role of player
engagement as a major factor in user experience and enjoyment. This encouraged
a greater investment in new types of game controllers such as the WiiMote, Rock
Band instruments and the Kinect. However, the native software of these
controllers was not originally designed to be used in other game applications.
This work addresses this issue by building a middleware framework, which maps
body poses or voice commands to actions in any game. This not only warrants a
more natural and customized user-experience but it also defines an
interoperable virtual controller. In this version of the framework, body poses
and voice commands are respectively recognized through the Kinect's built-in
cameras and microphones. The acquired data is then translated into the native
interaction scheme in real time using a lightweight method based on spatial
restrictions. The system is also prepared to use Nintendo's Wiimote as an
auxiliary and unobtrusive gamepad for physically or verbally impractical
commands. System validation was performed by analyzing the performance of
certain tasks and examining user reports. Both confirmed this approach as a
practical and alluring alternative to the game's native interaction scheme. In
sum, this framework provides a game-controlling tool that is totally
customizable and very flexible, thus expanding the market of game consumers.Comment: WorldCIST'13 Internacional Conferenc
GUI system for Elders/Patients in Intensive Care
In the old age, few people need special care if they are suffering from
specific diseases as they can get stroke while they are in normal life routine.
Also patients of any age, who are not able to walk, need to be taken care of
personally but for this, either they have to be in hospital or someone like
nurse should be with them for better care. This is costly in terms of money and
man power. A person is needed for 24x7 care of these people. To help in this
aspect we purposes a vision based system which will take input from the patient
and will provide information to the specified person, who is currently may not
in the patient room. This will reduce the need of man power, also a continuous
monitoring would not be needed. The system is using MS Kinect for gesture
detection for better accuracy and this system can be installed at home or
hospital easily. The system provides GUI for simple usage and gives visual and
audio feedback to user. This system work on natural hand interaction and need
no training before using and also no need to wear any glove or color strip.Comment: In proceedings of the 4th IEEE International Conference on
International Technology Management Conference, Chicago, IL USA, 12-15 June,
201
Exploring heritage through time and space : Supporting community reflection on the highland clearances
On the two hundredth anniversary of the Kildonan clearances, when people were forcibly removed from their homes, the Timespan Heritage centre has created a program of community centred work aimed at challenging pre conceptions and encouraging reflection on this important historical process. This paper explores the innovative ways in which virtual world technology has facilitated community engagement, enhanced visualisation and encouraged reflection as part of this program. An installation where users navigate through a reconstruction of pre clearance Caen township is controlled through natural gestures and presented on a 300 inch six megapixel screen. This environment allows users to experience the past in new ways. The platform has value as an effective way for an educator, artist or hobbyist to create large scale virtual environments using off the shelf hardware and open source software. The result is an exhibit that also serves as a platform for experimentation into innovative ways of community co-creation and co-curation.Postprin
From virtual demonstration to real-world manipulation using LSTM and MDN
Robots assisting the disabled or elderly must perform complex manipulation
tasks and must adapt to the home environment and preferences of their user.
Learning from demonstration is a promising choice, that would allow the
non-technical user to teach the robot different tasks. However, collecting
demonstrations in the home environment of a disabled user is time consuming,
disruptive to the comfort of the user, and presents safety challenges. It would
be desirable to perform the demonstrations in a virtual environment. In this
paper we describe a solution to the challenging problem of behavior transfer
from virtual demonstration to a physical robot. The virtual demonstrations are
used to train a deep neural network based controller, which is using a Long
Short Term Memory (LSTM) recurrent neural network to generate trajectories. The
training process uses a Mixture Density Network (MDN) to calculate an error
signal suitable for the multimodal nature of demonstrations. The controller
learned in the virtual environment is transferred to a physical robot (a
Rethink Robotics Baxter). An off-the-shelf vision component is used to
substitute for geometric knowledge available in the simulation and an inverse
kinematics module is used to allow the Baxter to enact the trajectory. Our
experimental studies validate the three contributions of the paper: (1) the
controller learned from virtual demonstrations can be used to successfully
perform the manipulation tasks on a physical robot, (2) the LSTM+MDN
architectural choice outperforms other choices, such as the use of feedforward
networks and mean-squared error based training signals and (3) allowing
imperfect demonstrations in the training set also allows the controller to
learn how to correct its manipulation mistakes
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