Dan Ionescu

3-D object model recovery from 2-D images using structured light

Three dimensional (3-D) object models are currently used in CAD/CAM, robotics, remote sensing, etc. The models (images) can be either directly acquired by using special devices such as range finders, CTR scanners, etc. or they can be recovered from a series of 2-D images of the object. In this paper, the authors propose a method for determining a set of reference pixels in two simultaneous views of the same object, using two cameras, by projecting a pseudo-random encoded grid on the object. The grid nodes and their encoding values are extracted from 2-D images by applying first a smoothing and then a watershed algorithm. The pseudo-random information encoded in the grid nodes is used to match corresponding sets of points of the two 2-D images. The set of matched points are further used to calculate the disparity of each point of the object surface. Experimental examples illustrate the performance of this simple and elegant technique.

An intelligent gesture interface for controlling TV sets and set-top boxes

The control of computers and electronics through hand gestures has gained significant industry and academic attention lately for the usability benefits and convenience that it offers users. Of particular research interest has been the control of living room environments containing televisions and set-top boxes. However, existing research has failed to provide a flexible solution for controlling such devices by hand gestures. They have used cameras that are sensitive to environmental factors such as lighting or that have unreasonable calibration demands. Additionally, the gesture processing techniques used so far have imposed considerable computational burden and have not provided a consistent and compelling TV control experience for a large variety of users and their homes. In this paper, the data returned from a custom 3D depth camera and a customizable gesture language is used to create an intelligent gesture interface for the control of TVs and set-top boxes. By using an infrared blaster to emit the commands typical of a physical remote, any television set or set-top box can be controlled to perform actions such as turning the TV on, changing the volume, muting the sound or changing the channel. Finally, a test setup is presented where a common television and a satellite receiver are controlled exclusively through hand gestures.

3D object model recovery from 2D images using structured light

Three-dimensional (3-D) object models are currently used in CAD/CAM, robotics, remote sensing, etc. The models (images) can be either directly acquired by using special devices such as range finders, CTR scanners, etc., or they can be recovered from a series of two-dimensional (2-D) images of the object. In this paper, the authors propose a method for determining a set of reference pixels in two simultaneous views of the same object, using two cameras, by projecting a pseudorandom encoded grid on the object. The grid nodes and their encoding values are extracted from 2-D images by applying first a smoothing and then a watershed algorithm. The pseudorandom information encoded in the grid nodes is used to match corresponding sets of points of the two 2-D images. The set of matched points are further used to calculate the disparity of each point of the object surface. Experimental examples illustrate the performance of this simple and elegant technique.

A high precision 3D object reconstruction method using a color coded grid and NURBS

A high-precision technique for reconstructing three-dimensional (3D) objects from its one-camera 2D views and using a color-coded structured light is described. The method does not require any a-priori knowledge of the absolute positioning and orientation of the camera, nor of a point in the scene. However a calibration process precedes the 3D reconstruction algorithm leading to a high-precision calculation of the position of the camera. The structured light, which is pseudo-randomly color-encoded, is used to determine unique points and lines on the surface of the object. The lines once extracted from a view of the object, are used for the determination of non-uniform rational Bezier splines (NURBS) curves to generate the surface of the object. The precision of the technique depends on the adaptation of the sampling rate of the structured light to the surface of the object. In a recent test, the precision of 7 tau (thousands of an inch) was achieved with a relatively smooth object. The paper describes only the 3D reconstruction process and not the integration of multiple views into one single 3D image of the object.

A real-time adaptive control of autonomic computing environments

Autonomic computing has received a great deal of attention from the research community in recent years. Many techniques have been proposed to monitor, analyze, and change the system under observation, but less attention has been paid to adapting the autonomic computing loop itself. Based on previous results on the design and implementation of a reference real-time architecture for autonomic computing, a self-adapting loop based on system-specific adaptation knowledge, which includes the types and properties of autonomic computing components, behavioural constraints, and strategies for adaptation is proposed in this paper. The proposed system is an integral part of the real-time system that controls the behaviour of the computing environment, evaluating its global behaviour using criteria that take into account the mathematical description of the time variation of the number of users in the system. Based on this evaluation, the adaptive system changes the control structure of the autonomic computing environment by replacing its controller with one matching the user time variation law. Elements of the self-adapting loop and the tradeoff of introducing additional overhead to the autonomic computing processes are discussed. A case study illustrates the self-adapting technique proposed.

A testbed and research network for next generation services over next generation networks

The complexity of todays data communication networks necessitates complete, realistic and sophisticated testing grounds for verifying and validating their functionality. Network testing grounds are restricted to laboratories and environments isolated from real life scenarios. Testing in production and commercial networks is typically forbidden since they present a high degree of risk factors for service availability. Additionally, the majority of todays communication network testbeds lack the scale and flexibility needed to properly represent a true networking environment. Before deploying live networks there is a need to have a network testing environment scalable and flexible enough where issues such as: network design, vendor interoperability, endurance, multiprotocol layer interconnectivity, a vendors specific implementations of standards and network design viability have been verified to meet the requirements. In this paper a design and implementation of a next generation network is described, where both testing and production traffic coexist. NCIT*net 2 is an optical transmission network supporting end-to-end services over technologies such as Ethernet, SONET, MPLS and DWDM. The paper also discusses key technology aspects related to the functionality of equipment and network from a service point of view. These include the physical layer and network operation, as well as architecture and control. The testbed network is used for the deployment of networking services over the above technologies in order to verify service implementation, provisioning and assurance of quality of service requirements. This network also allows testing and evaluating systems, subsystems and components from different vendors in various interconnections. The paper goes further to describe, as an example, the tests designed and implemented for the analysis of MPLS based services over next generation networks.

Towards a Real-Time Reference Architecture for Autonomic Systems

Autonomic computing aims to embed automation in IT management software such that it can adapt to changes in the configuration, provisioning, protection, and resource utilization variations of the IT infrastructure at run time. It is, therefore, almost natural to consider this control software framework as being designed with control principles in mind. One of the research trends considers autonomic computing as a control system that resolves constraints related to the optimal usage of resources based on external requests made by users or processes in a reactive way. In this paper, a real-time reference architecture is introduced in which components implementing functions of realtime system elements or blocks such as transducers, controllers, and actuators are designed. The architecture of the autonomic computing software also contains components that implement functionalities specific to real-time systems. The transducers, controllers, and actuators are thus connected via realtime pattern components such as concurrency, priority, and reliability patterns.

A Collaborative Cloud-Based Multimedia Sharing Platform for Social Networking Environments

The amount of multimedia content on the internet has been growing at a remarkable rate, and users are increasingly looking to share online media with colleagues and friends on social networks. Several commercial and academic solutions have attempted to make it easier to share this large variety of online content with others, but they are generally limited to sending links. Existing products have not been able to provide a scalable cloud-based system that synchronizes disparate web content among many users in real-time. Additionally, they have lacked a platform with a modular architecture that can be extended by developers to support new sources of online media. In this paper, a cloud-based software architecture for a multimedia collaboration platform is introduced. The platform is accessible from a typical web browser and allows users to collaborate over webcam chat while viewing videos, photos, maps, documents, and listening to music, all in real-time. As examples, it is shown how a distributed system called Watch Together was deployed to real users within Facebook and an e-learning environment. Usage data is provided from both deployments and observations are made on how users share and consume real-time multimedia content.

A Multimodal Interaction Method that Combines Gestures and Physical Game Controllers

Motion-based control of video games has gained significant attention from both academic and industrial research groups for the unique interactive experiences it offers. Of particular research interest has been the control of games through gesture-based interfaces enabled by 3D cameras that have recently been made affordable. However, existing research has yet to combine the benefits of a 3D camera with those of a physical game controller in a way that uses accurate gesture and controller tracking to provide six degrees of freedom and one-to-one correspondence between the real-world 3D space and the virtual environment. This paper presents a natural man-machine interaction method whereby a user is able to control a virtual space by using one hand to perform gestures and the other hand to wield a physical controller. The data returned from a custom 3D depth camera is used to obtain not only hand gestures (number of fingers and their angles), but also the absolute position of the physical controller. This 3D data is then combined with the orientation data returned by the accelerometers and gyroscopes within the physical controller. The controller data is fused in real-time into a composite transformation matrix that is applied to a 3D object. Two game prototypes are presented that combine hand gestures and a physical controller to create an entirely new level of interactive gaming.

On packet loss estimation for virtual private networks services

When provisioning the quantitative QoS based VPN services over packet switched networks, parameters such as packet loss, delay and delay jitter, besides the required bandwidth, have to be guaranteed. While the bandwidth is easier to guarantee during the lifetime of a VPN service, maintaining a value of the loss parameter below a preset value presents serious difficulties. Thus one of the main issues to be solved is to estimate the packet loss parameter effectively and accurately. Linking the stochastic characteristics of the traffic process to the loss probability has been examined as a solution under various contexts. Based on the large deviation theory (LDT), two types of asymptotic loss estimators have been studied extensively: the large buffer asymptotic and the large number of source asymptotic. This paper explores the application of the above estimators to the core links which aggregates lots of VPN services. To reduce the computational complexity, aggregate traffic approximation estimator is employed instead on the latter of the study. Firstly, the two practical estimators are derived based on LDT and Gaussian traffic model. Then their performances are evaluated in the live MPLS VPN network. Conclusion and suggestion for future research are formulated at the end of this paper