28,990 research outputs found
Remote Real-Time Collaboration Platform enabled by the Capture, Digitisation and Transfer of Human-Workpiece Interactions
In this highly globalised manufacturing ecosystem, product design and verification activities, production and inspection processes, and technical support services are spread across global supply chains and customer networks. Therefore, a platform for global teams to collaborate with each other in real-time to perform complex tasks is highly desirable. This work investigates the design and development of a remote real-time collaboration platform by using human motion capture technology powered by infrared light based depth imaging sensors borrowed from the gaming industry. The unique functionality of the proposed platform is the sharing of physical contexts during a collaboration session by not only exchanging human actions but also the effects of those actions on the task environment. This enables teams to remotely work on a common task problem at the same time and also get immediate feedback from each other which is vital for collaborative design, inspection and verifications tasks in the factories of the future
Visual Localisation of Mobile Devices in an Indoor Environment under Network Delay Conditions
Current progresses in home automation and service robotic environment have
highlighted the need to develop interoperability mechanisms that allow a
standard communication between the two systems. During the development of the
DHCompliant protocol, the problem of locating mobile devices in an indoor
environment has been investigated. The communication of the device with the
location service has been carried out to study the time delay that web services
offer in front of the sockets. The importance of obtaining data from real-time
location systems portends that a basic tool for interoperability, such as web
services, can be ineffective in this scenario because of the delays added in
the invocation of services. This paper is focused on introducing a web service
to resolve a coordinates request without any significant delay in comparison
with the sockets
PlaceRaider: Virtual Theft in Physical Spaces with Smartphones
As smartphones become more pervasive, they are increasingly targeted by
malware. At the same time, each new generation of smartphone features
increasingly powerful onboard sensor suites. A new strain of sensor malware has
been developing that leverages these sensors to steal information from the
physical environment (e.g., researchers have recently demonstrated how malware
can listen for spoken credit card numbers through the microphone, or feel
keystroke vibrations using the accelerometer). Yet the possibilities of what
malware can see through a camera have been understudied. This paper introduces
a novel visual malware called PlaceRaider, which allows remote attackers to
engage in remote reconnaissance and what we call virtual theft. Through
completely opportunistic use of the camera on the phone and other sensors,
PlaceRaider constructs rich, three dimensional models of indoor environments.
Remote burglars can thus download the physical space, study the environment
carefully, and steal virtual objects from the environment (such as financial
documents, information on computer monitors, and personally identifiable
information). Through two human subject studies we demonstrate the
effectiveness of using mobile devices as powerful surveillance and virtual
theft platforms, and we suggest several possible defenses against visual
malware
A middleware for a large array of cameras
Large arrays of cameras are increasingly being employed for producing high quality image sequences needed for motion analysis research. This leads to the logistical problem with coordination and control of a large number of cameras. In this paper, we used a lightweight multi-agent system for coordinating such camera arrays. The agent framework provides more than a remote sensor access API. It allows reconfigurable and transparent access to cameras, as well as software agents capable of intelligent processing. Furthermore, it eases maintenance by encouraging code reuse. Additionally, our agent system includes an automatic discovery mechanism at startup, and multiple language bindings. Performance tests showed the lightweight nature of the framework while validating its correctness and scalability. Two different camera agents were implemented to provide access to a large array of distributed cameras. Correct operation of these camera agents was confirmed via several image processing agents
Human-Machine Interface for Remote Training of Robot Tasks
Regardless of their industrial or research application, the streamlining of
robot operations is limited by the proximity of experienced users to the actual
hardware. Be it massive open online robotics courses, crowd-sourcing of robot
task training, or remote research on massive robot farms for machine learning,
the need to create an apt remote Human-Machine Interface is quite prevalent.
The paper at hand proposes a novel solution to the programming/training of
remote robots employing an intuitive and accurate user-interface which offers
all the benefits of working with real robots without imposing delays and
inefficiency. The system includes: a vision-based 3D hand detection and gesture
recognition subsystem, a simulated digital twin of a robot as visual feedback,
and the "remote" robot learning/executing trajectories using dynamic motion
primitives. Our results indicate that the system is a promising solution to the
problem of remote training of robot tasks.Comment: Accepted in IEEE International Conference on Imaging Systems and
Techniques - IST201
Monitoring wild animal communities with arrays of motion sensitive camera traps
Studying animal movement and distribution is of critical importance to
addressing environmental challenges including invasive species, infectious
diseases, climate and land-use change. Motion sensitive camera traps offer a
visual sensor to record the presence of a broad range of species providing
location -specific information on movement and behavior. Modern digital camera
traps that record video present new analytical opportunities, but also new data
management challenges. This paper describes our experience with a terrestrial
animal monitoring system at Barro Colorado Island, Panama. Our camera network
captured the spatio-temporal dynamics of terrestrial bird and mammal activity
at the site - data relevant to immediate science questions, and long-term
conservation issues. We believe that the experience gained and lessons learned
during our year long deployment and testing of the camera traps as well as the
developed solutions are applicable to broader sensor network applications and
are valuable for the advancement of the sensor network research. We suggest
that the continued development of these hardware, software, and analytical
tools, in concert, offer an exciting sensor-network solution to monitoring of
animal populations which could realistically scale over larger areas and time
spans
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