Emotion Recognition in Human-Computer Interaction

The authors are concerned with the development of computer systems that are capable of using information from faces and voices to recognise people's emotions in real-life situations. The paper addresses the nature of the challenges that lie ahead, and provides an assessment of the progress that has been made in the areas of signal processing and analysis techniques (with regard to speech and face), and the psychological and linguistic analyses of emotion. Ongoing developmental work by the authors in each of these areas is described.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Manufacturing System Simulation & Human Robot Interaction in VR:Manufacturing system simulation: Methodologies, software tools, case study in transportation design

Virtual Reality techniques are relatively new, having experienced significant development only during the last few years, in accordance with the progress achieved by computer science and hardware and software technologies. The study of such advanced design systems has led to the realization of an immersive environment in which new procedures for the evaluation of product prototypes, ergonomics and manufacturing operations have been simulated. The application of the environment realized to robotics, ergonomics, plant simulations and maintainability verifications has allowed us to highlight the advantages offered by a design methodology: the possibility of working on the industrial product in the first phase of conception; of placing the designer in front of the virtual reproduction of the product in a realistic way; and of interacting with the same concept. The aim of this book is to present an updated vision of VM through different aspects. We will describe the trends and results achieved in the automotive, aerospace and railway fields, in terms of the Digital Product Creation Process to design the product and the manufacturing process.

Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics

In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

Evaluating a Computer System that Converses Fluently with People

The SAL system embodies a new kind of human-computer interaction, where a person and a computer carry out a fluent, emotionally coloured conversation. Because that kind of capability is new, evaluating systems that have it is a new challenge. This paper outlines techniques that have been developed to evaluate SAL interactions, and uses the case to highlight the range of variables that become relevant in dealing with systems of this order of complexity.

Emotional speech: towards a new generation of databases

Research on speech and emotion is moving from a period of exploratory research into one where there is a prospect of substantial applications, notably in human-computer interaction. Progress in the area relies heavily on the development of appropriate databases. This paper addresses the issues that need to be considered in developing databases of emotional speech, and shows how the challenge of developing apropriate databases is being addressed in three major recent projects - the Belfast project, the Reading-Leeds project and the CREST-ESP project. From these and other studies the paper draws together the tools and methods that have been developed, addresses the problems that arise and indicates the future directions for the development of emotional speech databases.

A machine vision approach to the grading of crushed aggregate

The grading of crushed aggregate is carried out usually by sieving. We describe a new image-based approach to the automatic grading of such materials. The operational problem addressed is where the camera is located directly over a conveyor belt. Our approach characterizes the information content of each image, taking into account relative variation in the pixel data, and resolution scale. In feature space, we find very good class separation using a multidimensional linear classifier. The innovation in this work includes (i) introducing an effective image-based approach into this application area, and (ii) our supervised classification using wavelet entropy-based features.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

Second-Order Training of Adaptive Critics for Online Process Control

A new algorithm for training of nonlinear optimal neuro-controllers (in the form of the model-free, action-dependent, adaptive critic paradigm). Overcomes problems with existing stochastic backpropagation training: need for data storage, parameter shadowing and poor convergence, offering significant benefits for online applications.

Making the law accessible to non-lawyers: effects of different kinds of expertise on perceived usability of online legal information services

To help design an environment in which professionals without legal training can make effective use of public sector legal information on planning and the environment - for Add-Wijzer, a European e-government project - we evaluated their perceptions of usefulness and usability. In concurrent think-aloud usability tests, lawyers and non-lawyers carried out information retrieval tasks on a range of online legal databases. We found that non-lawyers reported twice as many difficulties as those with legal training (p = 0.001), that the number of difficulties and the choice of database affected successful completion, and that the non-lawyers had surprisingly few problems understanding legal terminology. Instead, they had more problems understanding the syntactical structure of legal documents and collections. The results support the constraint attunement hypothesis (CAH) of the effects of expertise on information retrieval, with implications for the design of systems to support the effective understanding and use of information.