This document is the first issue of the BIOVISION roadmap for the future of biometrics in Europe through to 2010. It offers a portfolio of techniques, viewpoints and scenarios to support future initiatives by national and European research organisations. A list of 38 prioritised research challenges forms the set of recommendations to the European Commission to support further R&D in these key technologies. Many of the recommendations look forward to the work programme of the European Biometric Forum.
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A succesful design, deployment and operation of biometric systems depends highly on the results for existing biometrical technologies and components. These existing technologies as well as new solutions need to be evaluated on their performance. However it is often forgotten that the biometric (iris, finger, face e.g.) is only one part of a fully deployed application. As biometric (sub)systems are often not designed with security and or privacy in mind, system integrators will need to address the requirements of the deployed application in this light. The fears and concerns of a significant segment of the user population need to be addressed as early as possible in the design process, to ensure that appropriate mechanisms are in place to reassure such users. These concerns may relate to privacy or to safety issues, which may be adressed in part through legal and regulatory measures.
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Embedded systems and ambient technology enable users to interact at any time and anywhere. In the BASIS project for identity management, CWI investigates transparent biometrics in home environments. Possible application areas are user profiling for shopping , listening to one's favourite music and operating gadgets and appliances in the home.
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In this paper we compare the effects of using three game user research methodologies to assist in shaping levels for a 2-D platformer game, and illustrate how the use of such methodologies can help level designers to make more informed decisions in an otherwise qualitative oriented design process. Game user interviews, game metrics and psychophysiology (biometrics) were combined in pairs to gauge usefulness in small-scale commercial game development scenarios such as the casual game industry. Based on the recommendations made by the methods, three sample levels of a Super Mario clone were improved and the opinions of a second sample of users indicated the success of these changes. We conclude that user interviews provide the clearest indications for improvement among the considered methodologies while metrics and biometrics add different types of information that cannot be obtained otherwise.
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Learning is all about feedback. Runners, for example, use apps like the RunKeeper. Research shows that apps like that enhance engagement and results. And people think it is fun. The essence being that the behavior of the runner is tracked and communicated back to the runner in a dashboard. We wondered if you can reach the same positive effect if you had a dashboard for Study-behaviour. For students. And what should you measure, track and communicate? We wondered if we could translate the Quantified Self Movement into a Quantified Student. So, together with students, professors and companies we started designing & building Quantified Student Apps. Apps that were measuring all kinds of study-behaviour related data. Things like Time On Campus, Time Online, Sleep, Exercise, Galvanic Skin Response, Study Results and so on. We developed tools to create study – information and prototyped the Apps with groups of student. At the same time we created a Big Data Lake and did a lot of Privacy research. The Big Difference between the Quantified Student Program and Learning Analytics is that we only present the data to the student. It is his/her data! It is his/her decision to act on it or not. The Quantified Student Apps are designed as a Big Mother never a Big Brother. The project has just started. But we already designed, created and learned a lot. 1. We designed and build for groups of prototypes for Study behavior Apps: a. Apps that measure sleep & exercise and compare it to study results, like MyRhytm; b. Apps that measure study hours and compare it to study results, like Nomi; c. Apps that measure group behavior and signal problems, like Groupmotion; d. Apps that measure on campus time and compare it with peers, like workhorse; 2. We researched student fysics to see if we could find his personal Cup-A-Soup-Moment (meaning, can we find by looking at his/her biometrics when the concentration levels dip?); 3. We created a Big Data lake with student data and Open Data and are looking for correlation and causality there. We already found some interesting patterns. In doing so we learned a lot. We learned it is often hard to acquire the right data. It is hard to create and App or a solution that is presenting the data in the right way and presents it in a form of actionable information. We learned that health trackers are still very inprecise. We learned about (and solved some) challenges surrounding privacy. Next year (2017) we will scale the most promising prototype, measure the effects, start a new researchproject and continu working on our data lake. Things will be interesting, and we will blog about it on www.quantifiedstudent.nl.
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Key factors in the public acceptance of biometric systems are non-intrusiveness, ease of use, and trust. In this paper we propose a biometric identity verification system consisting of a non-intrusive virtual mirror interface, and a face verifier using fractal coding to store the biometric template on a smart-card. The virtual mirror interface assists the user to obtain a frontal face image. The limited memory requirements of the fractal template and processing requirements of fractal decoding enable the implementation of the verification procedure on a smart-card. This set-up facilitates non-intrusive and easy to use biometric verification, and provides trust by adding a visualization to the biometric yes/no decision. Since the system does not require user assistance, it enables secure access over the Internet.
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