Ambient Intelligence is an emerging research field that aims to make many of the everyday activities of people easier and more efficient. This new paradigm gives rise to opportunities for novel, more efficient interactions with computing systems. At a technical level, the vision of Ambient Intelligence is realized by the seamless confluence of diverse computing platforms. In this context, a software framework (middleware) is essential to enable heterogeneous computing systems to interoperate. In this paper we first consider the basic requirements of a middleware that can effectively support the construction of Ambient Intelligence environments. Subsequently, we present a brief survey of existing, general-purpose middleware systems and evaluate them in terms of their suitability for serving as the low-level communication platform of an Ambient Intelligence middleware. Finally, we argue that an Object-Oriented middleware such as the Common Request Broker Architecture (CORBA) is most suited for basing a middleware for Ambient Intelligence environments.
In this paper, the application of computer vision techniques to the localization of multiple persons in a relatively wide gaming terrain is presented. Multiple views are employed both for terrain coverage, but most importantly, for treatment of occlusions. Through the appropriate selection of lightweight operations and acceleration strategies, an adequate frame rate is achieved despite the large volume of input data. The resulting system is employed in the development of multiplayer entertainment applications, which are demonstrated and evaluated.
We present the development of a multi-touch display based on computer vision techniques. The developed system is built upon low cost, off-the-shelf hardware components and a careful selection of computer vision techniques. The resulting system is capable of detecting and tracking several objects that may move freely on the surface of a wide projection screen. It also provides additional information regarding the detected and tracked objects, such as their orientation, their full contour, etc. All of the above are achieved robustly, in real time and regardless of the visual appearance of what may be independently projected on the projection screen. We also present indicative results from the exploitation of the developed system in three application scenarios and discuss directions for further research.
This paper introduces the horizontal, interdisciplinary, crossthematic RTD Programme in the field of Ambient Intelligence which has recently been initiated by the Institute of Computer Science of the Foundation for Research and Technology – Hellas, aiming to contribute towards the creation and provision of pioneering human-centric AmI technologies and smart environments.