Shape Metrics Based on Elastic Deformations

Deformations of shapes and distances between shapes are an active research topic in computer vision. We propose an energy of infinitesimal deformations of continuous 1- and 2-dimensional shapes that is based on the elastic energy of deformed objects. This energy defines a shape metric which is inherently invariant with respect to Euclidean transformations and yields very natural deformations which preserve details. We compute shortest paths between planar shapes based on elastic deformations and apply our approach to the modeling of 2-dimensional shapes.

Probabilistic Models for Shapes as Continuous Curves

We develop new shape models by defining a standard shape from which we can explain shape deformation and variability. Currently, planar shapes are modelled using a function space, which is applied to data extracted from images. We regard a shape as a continuous curve and identified on the Wiener measure space whereas previous methods have primarily used sparse sets of landmarks expressed in a Euclidean space. The average of a sample set of shapes is defined using measurable functions which treat the Wiener measure as varying Gaussians. Various types of invariance of our formulation of an average are examined in regard to practical applications of it. The average is examined with relation to a Fréchet mean in order to establish its validity. In contrast to a Fréchet mean, however, the average always exists and is unique in the Wiener space. We show that the average lies within the range of deformations present in the sample set. In addition, a measurement, which we call a quasi-score, is defined in order to evaluate “averages” computed by different shape methods, and to measure the overall deformation in a sample set of shapes. We show that the average defined within our model has the least spread compared with methods based on eigenstructure. We also derive a model to compactly express shape variation which comprises the average generated from our model. Some examples of average shape and deformation are presented using well-known datasets and we compare our model to previous work.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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Convex Hodge Decomposition and Regularization of Image Flows

The total variation (TV) measure is a key concept in the field of variational image analysis. In this paper, we focus on vector-valued data and derive from the Hodge decomposition of image flows a definition of TV regularization for vector-valued data that extends the standard componentwise definition in a natural way. We show that our approach leads to a convex decomposition of arbitrary vector fields, providing a richer decomposition into piecewise harmonic fields rather than piecewise constant ones, and motion texture. Furthermore, our regularizer provides a measure for motion boundaries of piecewise harmonic image flows in the same way, as the TV measure does for contours of scalar-valued piecewise constant images.

Legal safeguards for privacy and data protection in ambient intelligence

To get the maximum benefit from ambient intelligence (AmI), we need to anticipate and react to possible drawbacks and threats emerging from the new technologies in order to devise appropriate safeguards. The SWAMI project took a precautionary approach in its exploration of the privacy risks in AmI and sought ways to reduce them. It constructed four “dark scenarios” showing possible negative implications of AmI, notably for privacy protection. Legal analysis of the depicted futures showed the shortcomings of the current legal framework in being able to provide adequate privacy protection in the AmI environment. In this paper, the authors, building upon their involvement in SWAMI research as well as the further advancement of EU privacy analysis, identify various outstanding issues regarding the legal framework that still need to be resolved in order to deal with AmI in an equitable and efficacious way. This article points out some of the lacunae in the legal framework and postulates several privacy-specific safeguards aimed at overcoming them.

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Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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Understanding and capturing people’s privacy policies in a mobile social networking application

A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards privacy as they interact with such an application, and to explore technologies that empower users to more effectively and efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present evaluations of these technologies in the context of one laboratory study and three field studies.

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Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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An exploratory study for analyzing interactional processes of group discussion: the case of a focus group interview

The purposes of this study are (a) to establish a measurement for evaluating conversational impressions of group discussions, and (b) to make an exploratory investigation on their interactional processes which may affect to form those impressions. The impression rating and factor analysis undertaken first give us four factors concerning conversational impressions of “focus group interviews (FGIs)”: conversational activeness, conversational sequencing, the attitudes of participants and the relationships of participants. In relation to the factors of conversational activeness and conversational sequencing in particular, the microanalysis of four selected topical scenes from our database further shows that the behavior of the moderator and the interviewees is organized not independently but with reference to each other. The study thus emphasizes the importance of the integration of quantitative and qualitative approaches towards human interactions.

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Back to the shed: gendered visions of technology and domesticity

One of the tropes of the age of ubiquitous computing is the migration of computation into new spaces. Domestic environments have been a particular focus of attention for many. However, these spaces are neither empty nor neutral. They are already populated by people and practices which shape both their physical form and cultural meaning. We want to consider here some questions of technology and domesticity. In order to give some critical perspective, we want to approach domestic space from the edge, and in particular, from the shed.

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Evolving strategy for a probabilistic game of imperfect information using genetic programming

We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.

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Utilizing shape retrieval in sketch synthesis

This article describes SR-Sketch, a sketch creation tool that can act both as a front-end visual query module to visual information retrieval systems and as an aid tool for fast image composition. The system allows the user to draw shapes on the computer screen using the mouse cursor. At any time during this process the user can query a shape database for similar shapes and then select the ones s/he thinks are more relevant. The system can then automatically align and replace user-drawn objects with the chosen database shapes in the user sketch. For any match between a sketch shape and a database shape, the application can provide a visual explanation of how and why two shapes are considered similar. Evaluation results show that the system achieves favorable results with respect to noise tolerance, speed and reliability. SR-Sketch is freely available for download and experimentation.

A dynamically reconfigurable stereoscopic/panoramic vision mobile robot head controlled from a virtual environment

We have built a mobile robotic platform that features an Active Robotic Head (ARH) with two high-resolution cameras that can be switched during robot operation between two configurations that produce respectively panoramic and stereoscopic images. Image disparity is used for improving the quality of the texture. The robot head switches dynamically, based on robot operation between the stereoscopic configuration and the panoramic configuration.

Weight-proportional Space Partitioning Using Adaptive Voronoi Diagrams

Traditional application of Voronoi diagrams for space partitioning results in Voronoi regions, each with a specific area determined by the generators’ relative locations and weights. Particularly in the area of information space (re)construction, however, there is a need for inverse solutions; i.e., finding weights that result in regions with predefined area ratios. In this paper, we formulate an adaptive Voronoi solution and propose a raster-based optimization method for finding the associated weight set. The solution consists of a combination of simple, fixed-point iteration with an optional spatial resolution refinement along the regions’ boundaries using quadtree decomposition. We present the corresponding algorithm and its complexity analysis. The method is successfully tested on a series of ideal–typical cases and the interactions between the adaptive technique and boundary resolution refinement are explored and assessed.

Connecting the family with awareness systems

Awareness systems have attracted significant research interest for their potential to support interpersonal relationships. Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system, for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight, picture-based communication can play in the range of communication media available.

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Finding cohesive clusters for analyzing knowledge communities

Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which finds cohesive foreground clusters embedded in a diffuse background, and use it to identify knowledge communities as foreground clusters of papers which share common citations. To analyze the evolution of these communities over time, we build predictive models with features based on the citation structure, the vocabulary of the papers, and the affiliations and prestige of the authors. Findings include that scientific knowledge communities tend to grow more rapidly if their publications build on diverse information and if they use a narrow vocabulary.

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Formal analysis of human operator behavioural patterns in interactive surveillance systems

An important area of Human Reliability Assessment in interactive systems is the ability to understand the causes of human error and to model their occurrence. This paper investigates a new approach to analysis of task failures based on patterns of operator behaviour, in contrast with more traditional event-based approaches. It considers, as a case study, a formal model of an Air Traffic Control system operator’s task which incorporates a simple model of the high-level cognitive processes involved. The cognitive model is formalised in the CSP process algebra. Various patterns of behaviour that could lead to task failure are described using temporal logic. Then a model-checking technique is used to verify whether the set of selected behavioural patterns is sound and complete with respect to the definition of task failure. The decomposition is shown to be incomplete and a new behavioural pattern is identified, which appears to have been overlooked in the informal analysis of the problem. This illustrates how formal analysis of operator models can yield fresh insights into how failures may arise in interactive systems.

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