An Immersive Telepresence System using RGB-D Sensors and Head Mounted Display

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to ef- fectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The highly interactive and flexible environment can capture and sustain more student attention than the traditional classroom setting and, thus, delivers a compelling experience to the students. Our main focus here is to investigate possible solutions for the system design and implementation and devise strategies for fast, efficient computation suitable for visual data processing and network transmission. We describe the technique and experiments in details and provide quantitative performance results, demonstrating our system can be run comfortably and reliably for different application scenarios. Our preliminary results are promising and demonstrate the potential for more compelling directions in cyberlearning.Comment: IEEE International Symposium on Multimedia 201

Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives

The importance of depth perception in the interactions that humans have within their nearby space is a well established fact. Consequently, it is also well known that the possibility of exploiting good stereo information would ease and, in many cases, enable, a large variety of attentional and interactive behaviors on humanoid robotic platforms. However, the difficulty of computing real-time and robust binocular disparity maps from moving stereo cameras often prevents from relying on this kind of cue to visually guide robots' attention and actions in real-world scenarios. The contribution of this paper is two-fold: first, we show that the Efficient Large-scale Stereo Matching algorithm (ELAS) by A. Geiger et al. 2010 for computation of the disparity map is well suited to be used on a humanoid robotic platform as the iCub robot; second, we show how, provided with a fast and reliable stereo system, implementing relatively challenging visual behaviors in natural settings can require much less effort. As a case of study we consider the common situation where the robot is asked to focus the attention on one object close in the scene, showing how a simple but effective disparity-based segmentation solves the problem in this case. Indeed this example paves the way to a variety of other similar applications

Machine Analysis of Facial Expressions

No abstract

Particulate airborne impurities

The cumulative effects of air pollutants are of principal concern in research on environmental protection in Sweden. Post-industrial society has imposed many limits on emitted air pollutants, yet the number of reports on the negative effects from them is increasing, largely due to human activity in the form of industrial emissions and increased traffic flows. Rising concerns over the health effects from airborne particulate matter (PM) stem from in vitro, in vivo, and cohort studies revealing effects of mostly negative nature. Full insight into the health effects from PM can only be achieved through practical investigation of the mode of toxicity from distinct types of particles and requires techniques for their identification, monitoring, and the production of model fractions for health studies. To this effect, comprehensive collection and chemical analysis of particulates at the origin of emission was performed in order to provide clearer insight into the nature of the particulates at exposure and add detail to aid risk assessment. Methods of capturing particles and analyzing their chemical nature were devised using scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS). Furthermore, taking the approach of in vitro cytotoxicity testing, nanoparticles of types typical to automotive emissions, were synthesized and extensively characterized using SEM-EDS, X-ray diffraction (XRD), transmission electron microscopy (TEM),dynamic light scattering (DLS), and nanoparticle tracking analysis (NTA). The produced model magnetite and palladium nanoparticles were found to induce toxicity in human pulmonary epithelial cells (A549 and PBEC) as well as impact severely on immunological and renal cells (221 B- and 293T-cells) in a dose-dependent manner

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available