506 research outputs found
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
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