DisC Diversity: Result Diversification based on Dissimilarity and Coverage

Recently, result diversification has attracted a lot of attention as a means to improve the quality of results retrieved by user queries. In this paper, we propose a new, intuitive definition of diversity called DisC diversity. A DisC diverse subset of a query result contains objects such that each object in the result is represented by a similar object in the diverse subset and the objects in the diverse subset are dissimilar to each other. We show that locating a minimum DisC diverse subset is an NP-hard problem and provide heuristics for its approximation. We also propose adapting DisC diverse subsets to a different degree of diversification. We call this operation zooming. We present efficient implementations of our algorithms based on the M-tree, a spatial index structure, and experimentally evaluate their performance.Comment: To appear at the 39th International Conference on Very Large Data Bases (VLDB), August 26-31, 2013, Riva del Garda, Trento, Ital

Activity related biometrics for person authentication

One of the major challenges in human-machine interaction has always been the development of such techniques that are able to provide accurate human recognition, so as to other either personalized services or to protect critical infrastructures from unauthorized access. To this direction, a series of well stated and efficient methods have been proposed mainly based on biometric characteristics of the user. Despite the significant progress that has been achieved recently, there are still many open issues in the area, concerning not only the performance of the systems but also the intrusiveness of the collecting methods. The current thesis deals with the investigation of novel, activity-related biometric traits and their potential for multiple and unobtrusive authentication based on the spatiotemporal analysis of human activities. In particular, it starts with an extensive bibliography review regarding the most important works in the area of biometrics, exhibiting and justifying in parallel the transition that is performed from the classic biometrics to the new concept of behavioural biometrics. Based on previous works related to the human physiology and human motion and motivated by the intuitive assumption that different body types and different characters would produce distinguishable, and thus, valuable for biometric verification, activity-related traits, a new type of biometrics, the so-called prehension biometrics (i.e. the combined movement of reaching, grasping activities), is introduced and thoroughly studied herein. The analysis is performed via the so-called Activity hyper-Surfaces that form a dynamic movement-related manifold for the extraction of a series of behavioural features. Thereafter, the focus is laid on the extraction of continuous soft biometric features and their efficient combination with state-of-the-art biometric approaches towards increased authentication performance and enhanced security in template storage via Soft biometric Keys. In this context, a novel and generic probabilistic framework is proposed that produces an enhanced matching probability based on the modelling of the systematic error induced during the estimation of the aforementioned soft biometrics and the efficient clustering of the soft biometric feature space. Next, an extensive experimental evaluation of the proposed methodologies follows that effectively illustrates the increased authentication potential of the prehension-related biometrics and the significant advances in the recognition performance by the probabilistic framework. In particular, the prehension biometrics related biometrics is applied on several databases of ~100 different subjects in total performing a great variety of movements. The carried out experiments simulate both episodic and multiple authentication scenarios, while contextual parameters, (i.e. the ergonomic-based quality factors of the human body) are also taken into account. Furthermore, the probabilistic framework for augmenting biometric recognition via soft biometrics is applied on top of two state-of-art biometric systems, i.e. a gait recognition (> 100 subjects)- and a 3D face recognition-based one (~55 subjects), exhibiting significant advances to their performance. The thesis is concluded with an in-depth discussion summarizing the major achievements of the current work, as well as some possible drawbacks and other open issues of the proposed approaches that could be addressed in future works.Open Acces

Uncharted territory: daylight performance and occupant behaviour in a live classroom environment

In 2013, in an effort to improve the visual environment in future schools, a UK regulation specified mandatory daylight evaluations using, for the first time, climate-based metrics. Existing research on the daylighting performance of classrooms is limited and challenged by poor light measurement instrumentation, as well as the practicalities of the ‘live’ classroom setting. This paper describes an ongoing project aimed at providing evidence that will improve the understanding of how building occupants perceive daylight; how they respond to daylight performance due to the building design; and how their needs and actions shape the actual daylight performance of classrooms. A mixed method qualitative and quantitative approach is presented for the investigation of the aforementioned in four classrooms located in two secondary schools in the UK. Previously mentioned challenges are addressed by employing a High Dynamic Range imaging technique for monitoring physical data and the behaviour (blind and electric light use) of the occupants. The challenges encountered in the current study are discussed

Biometric Keys for the Encryption of Multimodal Signatures

Electricity, electromagnetism & magnetis

Real-world validation of climate-based daylight metrics: mission impossible?

One of the criticisms of metrics founded on climate-based daylight modelling (CBDM) is that they are unverifiable in practice. This criticism received some attention following the decision in 2013 by the Education Funding Agency to make CBDM and the useful daylight illuminance (UDI) metric a mandatory requirement for the evaluation of designs submitted for the Priority Schools Building Programme. Some of the difficulties related to the validation of CBDM metrics apply also to daylight factors. However, several other challenges need to be addressed and practical solutions found before any attempt at validation of CBDM metrics can be made. This paper identifies those challenges and describes a framework for the practical evaluation of daylighting performance in real world settings, and thus a basis for the validation of CBDM metrics. The task of validation requires a conflation of state-of-the-art techniques in measurement and modelling. Measurement techniques under consideration include high dynamic range imaging and ‘smart sensors’. A key obstacle to real world validation in, say, classrooms is that it is often not possible to rely on measurements of illuminance taken on the horizontal plane because such locations are rarely free from disturbance during normal use. It becomes necessary therefore to measure illuminance at more reliable locations (e.g. walls) and use these as a proxy for illuminance performance on the horizontal. The relation between wall and desk performance is space-specific and can be determined using CBDM. The first steps towards practical application of this framework are described