Work at hand : an exploration of gesture in the context of work and everyday life to inform the design of gestural input devices

This research explores gestures used in the context of activities in the workplace and in everyday life in order to understand requirements and devise concepts for the design of gestural information applicances. A collaborative method of video interaction analysis devised to suit design explorations, the Video Card Game, was used to capture and analyse how gesture is used in the context of six different domains: the dentist's office; PDA and mobile phone use; the experimental biologist's laboratory; a city ferry service; a video cassette player repair shop; and a factory flowmeter assembly station. Findings are presented in the form of gestural themes, derived from the tradition of qualitative analysis but bearing some similarity to Alexandrian patterns. Implications for the design of gestural devices are discussed.

Virtual worlds in Australian and New Zealand higher education : remembering the past, understanding the present and imagining the future

3D virtual reality, including the current generation of multi-user virtual worlds, has had a long history of use in education and training, and it experienced a surge of renewed interest with the advent of Second Life in 2003. What followed shortly after were several years marked by considerable hype around the use of virtual worlds for teaching, learning and research in higher education. For the moment, uptake of the technology seems to have plateaued, with academics either maintaining the status quo and continuing to use virtual worlds as they have previously done or choosing to opt out altogether. This paper presents a brief review of the use of virtual worlds in the Australian and New Zealand higher education sector in the past and reports on its use in the sector at the present time, based on input from members of the Australian and New Zealand Virtual Worlds Working Group. It then adopts a forward-looking perspective amid the current climate of uncertainty, musing on future directions and offering suggestions for potential new applications in light of recent technological developments and innovations in the area.

Sistema de seguimento dos movimentos oculares para interface adaptada pessoa-máquina

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de redes de Comunicação e Multimédia

Virtual worlds in Australian and New Zealand higher education: Remembering the past, understanding the present and imagining the future

3D virtual reality, including the current generation of multi-user virtual worlds, has had a long history of use in education and training, and it experienced a surge of renewed interest with the advent of Second Life in 2003. What followed shortly after were several years marked by considerable hype around the use of virtual worlds for teaching, learning and research in higher education. For the moment, uptake of the technology seems to have plateaued, with academics either maintaining the status quo and continuing to use virtual worlds as they have previously done or choosing to opt out altogether. This paper presents a brief review of the use of virtual worlds in the Australian and New Zealand higher education sector in the past and reports on its use in the sector at the present time, based on input from members of the Australian and New Zealand Virtual Worlds Working Group. It then adopts a forward-looking perspective amid the current climate of uncertainty, musing on future directions and offering suggestions for potential new applications in light of recent technological developments and innovations in the area.

Fast robot voice interface through optimum-path forest

Voice-based user interfaces have been actively pursued aiming to help individuals with motor impairments, providing natural interfaces to communicate with machines. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for voice-based robot interface, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster. Experiments were conducted against Support Vector Machines, Neural Networks and a Bayesian classifier to show the OPF robustness. The proposed architecture provides high accuracy rates allied with low computational times. © 2012 IEEE.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Desarrollo del teclado virtual “Mokey” basado en gestos para personas con movilidad reducida: capa de sistema

La Realidad Aumentada forma parte de múltiples proyectos de investigación desde hace varios años. La unión de la información del mundo real y la información digital ofrece un sinfín de posibilidades. Las más conocidas van orientadas a los juegos pero, gracias a ello, también se pueden implementar Interfaces Naturales. En otras palabras, conseguir que el usuario maneje un dispositivo electrónico con sus propias acciones: movimiento corporal, expresiones faciales, etc. El presente proyecto muestra el desarrollo de la capa de sistema de una Interfaz Natural, Mokey, que permite la simulación de un teclado mediante movimientos corporales del usuario. Con esto, se consigue que cualquier aplicación de un ordenador que requiera el uso de un teclado, pueda ser usada con movimientos corporales, aunque en el momento de su creación no fuese diseñada para ello. La capa de usuario de Mokey es tratada en el proyecto realizado por Carlos Lázaro Basanta. El principal objetivo de Mokey es facilitar el acceso de una tecnología tan presente en la vida de las personas como es el ordenador a los sectores de la población que tienen alguna discapacidad motora o movilidad reducida. Ya que vivimos en una sociedad tan informatizada, es esencial que, si se quiere hablar de inclusión social, se permita el acceso de la actual tecnología a esta parte de la población y no crear nuevas herramientas exclusivas para ellos, que generarían una situación de discriminación, aunque esta no sea intencionada. Debido a esto, es esencial que el diseño de Mokey sea simple e intuitivo, y al mismo tiempo que esté dotado de la suficiente versatilidad, para que el mayor número de personas discapacitadas puedan encontrar una configuración óptima para ellos. En el presente documento, tras exponer las motivaciones de este proyecto, se va a hacer un análisis detallado del estado del arte, tanto de la tecnología directamente implicada, como de otros proyectos similares. Se va prestar especial atención a la cámara Microsoft Kinect, ya que es el hardware que permite a Mokey detectar la captación de movimiento. Tras esto, se va a proceder a una explicación detallada de la Interfaz Natural desarrollada. Se va a prestar especial atención a todos aquellos algoritmos que han sido implementados para la detección del movimiento, así como para la simulación del teclado. Finalmente, se va realizar un análisis exhaustivo del funcionamiento de Mokey con otras aplicaciones. Se va a someter a una batería de pruebas muy amplia que permita determinar su rendimiento en las situaciones más comunes. Del mismo modo, se someterá a otra batería de pruebas destinada a definir su compatibilidad con los diferentes tipos de programas existentes en el mercado. Para una mayor precisión a la hora de analizar los datos, se va a proceder a comparar Mokey con otra herramienta similar, FAAST, pudiendo observar de esta forma las ventajas que tiene una aplicación especialmente pensada para gente discapacitada sobre otra que no tenía este fin. ABSTRACT. During the last few years, Augmented Reality has been an important part of several research projects, as the combination of the real world and the digital information offers a whole new set of possibilities. Among them, one of the most well-known possibilities are related to games by implementing Natural Interfaces, which main objective is to enable the user to handle an electronic device with their own actions, such as corporal movements, facial expressions… The present project shows the development of Mokey, a Natural Interface that simulates a keyboard by user’s corporal movements. Hence, any application that requires the use of a keyboard can be handled with this Natural Interface, even if the application was not designed in that way at the beginning. The main objective of Mokey is to simplify the use of the computer for those people that are handicapped or have some kind of reduced mobility. As our society has been almost completely digitalized, this kind of interfaces are essential to avoid social exclusion and discrimination, even when it is not intentional. Thus, some of the most important requirements of Mokey are its simplicity to use, as well as its versatility. In that way, the number of people that can find an optimal configuration for their particular condition will grow exponentially. After stating the motivations of this project, the present document will provide a detailed state of the art of both the technologies applied and other similar projects, highlighting the Microsoft Kinect camera, as this hardware allows Mokey to detect movements. After that, the document will describe the Natural Interface that has been developed, paying special attention to the algorithms that have been implemented to detect movements and synchronize the keyboard. Finally, the document will provide an exhaustive analysis of Mokey’s functioning with other applications by checking its behavior with a wide set of tests, so as to determine its performance in the most common situations. Likewise, the interface will be checked against another set of tests that will define its compatibility with different softwares that already exist on the market. In order to have better accuracy while analyzing the data, Mokey’s interface will be compared with a similar tool, FAAST, so as to highlight the advantages of designing an application that is specially thought for disabled people.

Work at hand: an exploration of gesture in the context of work and everyday life to inform the design of gestural input devices

This research explores gestures used in the context of activities in the workplace and in everyday life in order to understand requirements and devise concepts for the design of gestural information appliances. A collaborative method of video interaction analysis devised to suit design explorations, the Video Card Game, was used to capture and analyse how gesture is used in the context of six different domains: the dentist's office; PDA and mobile phone use; the experimental biologist's laboratory; a city ferry service; a video cassette player repair shop; and a factory flowmeter assembly station. Findings are presented in the form of gestural themes, derived from the tradition of qualitative analysis but bearing some similarity to Alexandrian patterns. Implications for the design of gestural devices are discussed.

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

Using natural user interfaces for collaborative process modelling in virtual environments

Modelling business processes for analysis or redesign usually requires the collaboration of many stakeholders. These stakeholders may be spread across locations or even companies, making co-located collaboration costly and difficult to organize. Modern process modelling technologies support remote collaboration but lack support for visual cues used in co-located collaboration. Previously we presented a prototype 3D virtual world process modelling tool that supports a number of visual cues to facilitate remote collaborative process model creation and validation. However, the added complexity of having to navigate a virtual environment and using an avatar for communication made the tool difficult to use for novice users. We now present an evolved version of the technology that addresses these issues by providing natural user interfaces for non-verbal communication, navigation and model manipulation.

Using natural user interfaces for collaborative process modelling in virtual environments

A demo video showing the BPMVM prototype using several natural user interfaces, such as multi-touch input, full-body tracking and virtual reality.

Social NUI: Social perspectives in natural user interfaces

Natural User Interfaces (NUI) offer rich ways for interacting with the digital world that make innovative use of existing human capabilities. They include and often combine different input modalities such as voice, gesture, eye gaze, body interactions, touch and touchless interactions. However much of the focus of NUI research and development has been on enhancing the experience of individuals interacting with technology. Effective NUIs must also acknowledge our innately social characteristics, and support how we communicate with each other, play together, learn together and collaboratively work together. This workshop concerns the social aspects of NUI. The workshop seeks to better understand the social uses and applications of these new NUI technologies -- how we design these technologies for new social practices and how we understand the use of these technologies in key social contexts.

Towards an intelligent learning system for the natural born cyborg

We propose to design a Custom Learning System that responds to the unique needs and potentials of individual students, regardless of their location, abilities, attitudes, and circumstances. This project is intentionally provocative and future-looking but it is not unrealistic or unfeasible. We propose that by combining complex learning databases with a learner’s personal data, we could provide all students with a personal, customizable, and flexible education. This paper presents the initial research undertaken for this project of which the main challenges were to broadly map the complex web of data available, to identify what logic models are required to make the data meaningful for learning, and to translate this knowledge into simple and easy-to-use interfaces. The ultimate outcome of this research will be a series of candidate user interfaces and a broad system logic model for a new smart system for personalized learning. This project is student-centered, not techno-centric, aiming to deliver innovative solutions for learners and schools. It is deliberately future-looking, allowing us to ask questions that take us beyond the limitations of today to motivate new demands on technology.