Facial movement analysis in ASL

In the age of speech and voice recognition technologies, sign language recognition is an essential part of ensuring equal access for deaf people. To date, sign language recognition research has mostly ignored facial expressions that arise as part of a natural sign language discourse, even though they carry important grammatical and prosodic information. One reason is that tracking the motion and dynamics of expressions in human faces from video is a hard task, especially with the high number of occlusions from the signers’ hands. This paper presents a 3D deformable model tracking system to address this problem, and applies it to sequences of native signers, taken from the National Center of Sign Language and Gesture Resources (NCSLGR), with a special emphasis on outlier rejection methods to handle occlusions. The experiments conducted in this paper validate the output of the face tracker against expert human annotations of the NCSLGR corpus, demonstrate the promise of the proposed face tracking framework for sign language data, and reveal that the tracking framework picks up properties that ideally complement human annotations for linguistic research.

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Supporting ordering and consistency in a distributed Event Heap for Ubiquitous Computing

The Stanford Event Heap has been shown to provide appropriate support for constructing interactive workspace applications. Given this success it is natural to consider the Event Heap as a platform to support other classes of Ubiquitous Computing applications. In this paper we argue that the distributed, spontaneous nature of these applications places additional demands on the Event Heap that require extensions to both the engineering and API. Suitable extensions are described and their use to support a typical Ubicomp application is discussed.

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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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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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A vector gravitational force model for classification

The paper presents a decision algorithmic model called vector gravitational force model in the feature space. The algorithmic model, inspired by and similar to the Law of Universal Gravitation, is derived from the vector geometric analysis of the linear classifier and established in the feature space. Based on this algorithmic model, we propose a classification method called vector gravitational recognition. The proposed method is applied to the benchmark Glass Identification task in the UCI Database available from USA Forensic Science Service, and other two UCI benchmark tasks. The experimental and comparative results show that the proposed approach yields quite good results and outperforms some well known and recent approaches on the tasks, and other applications may benefit from ours.

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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Specifying and analyzing early requirements in Tropos

We present a framework that supports the formal verification of early requirements specifications. The framework is based on Formal Tropos, a specification language that adopts primitive concepts for modeling early requirements (such as actor, goal, and strategic dependency), along with a rich temporal specification language. We show how existing formal analysis techniques, and in particular model checking, can be adapted for the automatic verification of Formal Tropos specifications. These techniques have been implemented in a tool, called the T-Tool, that maps Formal Tropos specifications into a language that can be handled by the NuSMV model checker. Finally, we evaluate our methodology on a course-exam management case study. Our experiments show that formal analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tools.

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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E-redesigning of society: towards experiential connectivity of generations in Lithuania

The paper reflects on the unique experience of social and technological development in Lithuania since the regaining of independence as a newly reshaped society constructing a distinctive competitive IST-based model at global level. This has presented Lithuanian pattern of how to integrate different experiences and relations between generations in implementing complex information society approaches. The resulting programme in general is linked to the Lisbon objectives of the European Union. The experience of transitional countries in Europe, each different but facing some common problems, may be useful to developing countries in Africa.

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Using trust assumptions with security requirements

Assumptions are frequently made during requirements analysis of a system about the trustworthiness of its various components (including human components). These trust assumptions, whether implicit or explicit, affect the scope of the analysis, derivation of security requirements, and in some cases how functionality is realized. This paper presents trust assumptions in the context of analysis of security requirements. A running example shows how trust assumptions can be used by a requirements engineer to help define and limit the scope of analysis and to document the decisions made during the process. The paper concludes with a case study examining the impact of trust assumptions on software that uses the secure electronic transaction specification.

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Understanding Programming Languages

We document the influence on programming language semantics of the Platonism/formalism divide in the philosophy of mathematics.

Scientific models and ethical issues in hybrid bionic systems research

Research on hybrid bionic systems (HBSs) is still in its infancy but promising results have already been achieved in laboratories. Experiments on humans and animals show that artificial devices can be controlled by neural signals. These results suggest that HBS technologies can be employed to restore sensorimotor functionalities in disabled and elderly people. At the same time, HBS research raises ethical concerns related to possible exogenous and endogenous limitations to human autonomy and freedom. The analysis of these concerns requires reflecting on the availability of scientific models accounting for key aspects of sensorimotor coordination and plastic adaptation mechanisms in the brain.

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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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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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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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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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Online updating appearance generative mixture model for meanshift tracking

This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks an object by maximizing the similarity between the histogram in tracking window and a static histogram acquired at the beginning of tracking. The tracking therefore could fail if the appearance of the object varies substantially. In this paper, we assume the key appearances of the object can be acquired before tracking and the manifold of the object appearance can be approximated by piece-wise linear combination of these key appearances in histogram space. The generative process is described by a Bayesian graphical model. An Online EM algorithm is proposed to estimate the model parameters from the observed histogram in the tracking window and to update the appearance histogram. We applied this approach to track human head motion and to infer the head pose simultaneously in videos. Experiments verify that our online histogram generative model constrained by key appearance histograms alleviates the drifting problem often encountered in tracking with online updating, that the enhanced meanshift algorithm is capable of tracking object of varying appearances more robustly and accurately, and that our tracking algorithm can infer additional information such as the object poses. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

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Inverse multi-objective robust evolutionary design

In this paper, we present an Inverse Multi-Objective Robust Evolutionary (IMORE) design methodology that handles the presence of uncertainty without making assumptions about the uncertainty structure. We model the clustering of uncertain events in families of nested sets using a multi-level optimization search. To reduce the high computational costs of the proposed methodology we proposed schemes for (1) adapting the step-size in estimating the uncertainty, and (2) trimming down the number of calls to the objective function in the nested search. Both offline and online adaptation strategies are considered in conjunction with the IMORE design algorithm. Design of Experiments (DOE) approaches further reduce the number of objective function calls in the online adaptive IMORE algorithm. Empirical studies conducted on a series of test functions having diverse complexities show that the proposed algorithms converge to a set of Pareto-optimal design solutions with non-dominated nominal and robustness performances efficiently.

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