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    ABSTRACT: Export Date: 29 November 2012, Source: Scopus, doi: 10.1049/cp.2012.0437, Language of Original Document: English, Correspondence Address: Soyel, H.; Department of Computer Science, Queen Mary University of LondonUnited Kingdom; email: hsoyel@eecs.qmul.ac.uk
    IET Conference Publications; 01/2012
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    ABSTRACT: Experts must agree a set of acceptable ways to assess and present forensic evidence, says Norman Fenton.
    Nature 01/2011; 479(7371):36-7.
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    ABSTRACT: We present three different functional interpretations of intuitionistic linear logic ILL and show how these correspond to well-known functional interpretations of intuitionistic logic IL via embeddings of IL into ILL. The main difference from previous work of the second author is that in intuitionistic linear logic (as opposed to classical linear logic) the interpretations of !A are simpler and simultaneous quantifiers are no longer needed for the characterisation of the interpretations. We then compare our approach in developing these three proof interpretations with the one of de Paiva around the Dialectica category model of linear logic.
    12/2010;
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    ABSTRACT: We investigate the problem of estimating the ego-motion of a multicamera rig from two positions of the rig. We describe and compare two new algorithms for finding the 6 degrees of freedom (3 for rotation and 3 for translation) of the motion. One algorithm gives a linear solution and the other is a geometric algorithm that minimizes the maximum measurement error-the optimal L{infinity} solution. They are described in the context of the General Camera Model (GCM), and we pay particular attention to multicamera systems in which the cameras have nonoverlapping or minimally overlapping field of view. Many nonlinear algorithms have been developed to solve the multicamera motion estimation problem. However, no linear solution or guaranteed optimal geometric solution has previously been proposed. We made two contributions: 1) a fast linear algebraic method using the GCM and 2) a guaranteed globally optimal algorithm based on the L{infinity} geometric error using the branch-and-bound technique. In deriving the linear method using the GCM, we give a detailed analysis of degeneracy of camera configurations. In finding the globally optimal solution, we apply a rotation space search technique recently proposed by Hartley and Kahl. Our experiments conducted on both synthetic and real data have shown excellent results.
    IEEE Transactions on Software Engineering 06/2010; 32(6):1044-59.
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    ABSTRACT: In this paper, we present a motion segmentation algorithm for image sequences based on the Hadamard (or Schur) product of shape interaction matrices computed over a range of dimensions of the ambient space and using a spectral clustering algorithm. Most motion segmentation algorithms proposed to date are based on the use of a shape interaction matrix, obtained via factorization, since it encodes the essential information to segment independently moving rigid objects. However, so far, most studies have been limited to using a single shape interaction matrix to cluster the motions of different objects. In this paper, we propose to combine the shape interaction matrices computed for different subspace dimensions using the Hadamard product. The benefit of this approach is that the affinity of trajectories belonging to the same object is stressed while the affinity between trajectories belonging to different objects is diminished. Once the final shape interaction matrix is computed, we use a spectral clustering algorithm to segment the different motions. Experiments on the Hopkins 155 data set for both independent and articulated motions show that our new algorithm provides a lower miss-classification error rate, outperforming other state of the art algorithms.
    Motion and Video Computing, 2009. WMVC '09. Workshop on; 01/2010
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    ABSTRACT: We present a hybrid Bayesian network (HBN) framework to model the availability of renewable systems. We use an approximate inference algorithm for HBNs that involves dynamically discretizing the domain of all continuous variables and use this to obtain accurate approximations for the renewal or repair time distributions for a system. We show how we can use HBNs to model corrective repair time, logistics delay times and scheduled maintenance time distributions and combine these with time-to-failure distributions to derive system availability. Example models are presented and are accompanied by detailed descriptions of how repair (renewal) distributions might be modelled using HBNs.
    Engineering Applications of Artificial Intelligence - ENG APPL ARTIF INTELL. 01/2010;
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    ABSTRACT: This paper shows how recent Bayesian network (BN) algorithms can be used to model time to failure distributions and perform reliability analysis of complex systems in a simple unified way. The algorithms work for so-called hybrid BNs, which are BNs that can contain a mixture of both discrete and continuous variables. Our BN approach extends fault trees by defining the time-to-failure of the fault tree constructs as deterministic functions of the corresponding input components’ time-to-failure. This helps solve any configuration of static and dynamic gates with general time-to-failure distributions. Unlike other approaches (which tend to be restricted to using exponential failure distributions) our approach can use any parametric or empirical distribution for the time-to-failure of the system components. We demonstrate that the approach produces results equivalent to the state of the practice and art for small examples; more importantly our approach produces solutions hitherto unobtainable for more complex examples, involving non-standard assumptions.. The approach offers a powerful framework for analysts and decision makers to successfully perform robust reliability assessment. Sensitivity, uncertainty, diagnosis analysis, common cause failures and warranty analysis can also be easily performed within this framework.
    Reliability Engineering & System Safety. 01/2010;
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    ABSTRACT: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi's quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.
    Neurocomputing. 01/2010; 73:1840-1852.
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    ABSTRACT: Robot companions must be able to display social, affective behaviour. As a prerequisite for companionship, the ability to sustain long-term interactions with users requires companions to be endowed with affect recognition abilities. This paper explores application-dependent user states in a naturalistic scenario where an iCat robot plays chess with children. In this scenario, the role of context is investigated for the modelling of user states related both to the task and the social interaction with the robot. Results show that contextual features related to the game and the iCat's behaviour are successful in helping to discriminate among the identified states. In particular, state and evolution of the game and display of facial expressions by the iCat proved to be the most significant: when the user is winning and improving in the game her feeling is more likely to be positive and when the iCat displays a facial expression during the game the user's level of engagement with the iCat is higher. These findings will provide the foundation for a rigorous design of an affect recognition system for a game companion.
    Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on; 10/2009
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    ABSTRACT: This paper reviews some of the key challenges in affect recognition research for the purpose of designing affect sensitive social robots. An important requirement for a social robot is to be endowed with recognition abilities that vary according to the context of interaction. This paper presents an approach for the analysis of different affective cues depending on the distance at which user and robot interact.
    Image Analysis for Multimedia Interactive Services, 2009. WIAMIS '09. 10th Workshop on; 06/2009
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