CARTON Project: Do-It-Yourself Approach to Turn a Smartphone into a Smart Eyewear

International audienceThis paper presents a tool to transform a smartphone into a smart eyewear, named "CARTON", following a Do-It-Yourself (DIY) approach. The hardware prototype is made with very simple materials and regular tools we could find anywhere. It also includes a Software Development Kit (SDK) with samples in order to easily adapt or develop new mobile app compatible with this kind of device. By providing everything open-source and open-hardware, we intend to solve the reachability of technologies related to smart eyewear and aim to accelerate research around it. Users experiments were conducted in which participants were asked to create, by themselves, the CARTON's hardware part and perform usability tests with their own creation. Qualitative user feedback and quantitative results prove that CARTON is functional and feasible by anyone, without specific skills

Challenges in Developing Applications for Aging Populations

Elderly individuals can greatly benefit from the use of computer applications, which can assist in monitoring health conditions, staying in contact with friends and family, and even learning new things. However, developing accessible applications for an elderly user can be a daunting task for developers. Since the advent of the personal computer, the benefits and challenges of developing applications for older adults have been a hot topic of discussion. In this chapter, the authors discuss the various challenges developers who wish to create applications for the elderly computer user face, including age-related impairments, generational differences in computer use, and the hardware constraints mobile devices pose for application developers. Although these challenges are concerning, each can be overcome after being properly identified

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