The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio

Wearable and mobile devices

Information and Communication Technologies, known as ICT, have undergone dramatic changes in the last 25 years. The 1980s was the decade of the Personal Computer (PC), which brought computing into the home and, in an educational setting, into the classroom. The 1990s gave us the World Wide Web (the Web), building on the infrastructure of the Internet, which has revolutionized the availability and delivery of information. In the midst of this information revolution, we are now confronted with a third wave of novel technologies (i.e., mobile and wearable computing), where computing devices already are becoming small enough so that we can carry them around at all times, and, in addition, they have the ability to interact with devices embedded in the environment. The development of wearable technology is perhaps a logical product of the convergence between the miniaturization of microchips (nanotechnology) and an increasing interest in pervasive computing, where mobility is the main objective. The miniaturization of computers is largely due to the decreasing size of semiconductors and switches; molecular manufacturing will allow for “not only molecular-scale switches but also nanoscale motors, pumps, pipes, machinery that could mimic skin” (Page, 2003, p. 2). This shift in the size of computers has obvious implications for the human-computer interaction introducing the next generation of interfaces. Neil Gershenfeld, the director of the Media Lab’s Physics and Media Group, argues, “The world is becoming the interface. Computers as distinguishable devices will disappear as the objects themselves become the means we use to interact with both the physical and the virtual worlds” (Page, 2003, p. 3). Ultimately, this will lead to a move away from desktop user interfaces and toward mobile interfaces and pervasive computing

Wearable learning tools

In life people must learn whenever and wherever they experience something new. Until recently computing technology could not support such a notion, the constraints of size, power and cost kept computers under the classroom table, in the office or in the home. Recent advances in miniaturization have led to a growing field of research in ‘wearable’ computing. This paper looks at how such technologies can enhance computer‐mediated communications, with a focus upon collaborative working for learning. An experimental system, MetaPark, is discussed, which explores communications, data retrieval and recording, and navigation techniques within and across real and virtual environments. In order to realize the MetaPark concept, an underlying network architecture is described that supports the required communication model between static and mobile users. This infrastructure, the MUON framework, is offered as a solution to provide a seamless service that tracks user location, interfaces to contextual awareness agents, and provides transparent network service switching