We propose to construct a system for 3D face recognition. We propose to use photometric stereo for face reconstruction in order to by pass the problems of conventional stereo (that needs to solve the matching problem first), structured light (that does not supply colour information) and photometric stereo with spectrally distinct light sources (that relies on the assumption of uniformly coloured imaged objects). Photometric stereo (PS) can reproduce structural details and colour on a per pixel basis in a way that no other 3D system can. The proposed scheme will be appropriate for use in a controlled environment for authentication purposes, but also in a general environment e.g. the entrance of a public event. We shall use two routes: surface reconstruction from the data and direct extraction of facial characteristics from the PS set. In the first approach, once surface normal and albedo is recovered, images of the face may be synthetically rendered under arbitrary new pose and illumination conditions to allow novel viewing conditions. We also aim to use a new multi-scale facial feature matching approach in the recognition process, where facial features range from overall face and head shape to fine skin dermal topography, reflectance and texture. The latter may be thought of as a form of detailed surface bump map forming a unique skin-print or signature and represents a new approach. Hence both the 3D shape and 2D intensity data will be used in recognition or authentication tasks. We propose to use scalable methods for matching, so we can cope with large databases. 3D matching will be done with the newly proposed invaders algorithm which is FFT cross-correlation based, and more detailed matching will be done by using features and classifier combination. The novelty of our approach lies in the use of PS to extract 3D information, the use of detailed facial characteristics like moles, scratches, and skin texture, and in the design of the system so that it can operate while the person is moving, with minimum intrusion and maximum efficiency. We have two industrial collaborators who will contribute in system design, data gathering and exploitation and support from the Home Office. We shall evaluate our system following three possible scenaria: a face searched in the crowd (real time face recognition), a person has to be identified (off-line face recognition) and a person has to be checked against a claimed identity (face authentication). We shall install the first prototype system in the offices of one of our industrial partners in month 12, so that data can be collected. We envisage a door like structure with lights flashing in succession as a person walks through, while a camera is capturing images. We propose to investigate the optimal number of lights in terms of efficiency and accuracy of the reconstruction, and the option of using non-visible light to avoid problems with people sensitive to flashes. We shall also investigate the relationship between detail that has to be captured and the geometry of the construction.

This proposal aims to advance the state-of-the-art in 3D face recognition by means of a novel, non-intrusive and highly efficient skin reflectance capture technology. The techniques developed will, in-turn, enable rapid facial geometry analysis and enhanced recognition rates.Face recognition is currently a rapidly growing area of research within industry and academia. Indeed, 2D face recognition is now at a stage where a few industrial applications are possible. However, these methods, which just use a single 2D image of a face to perform the recognition, are excessively limited by the fact that the face becomes unrecognisable when variations such as pose, illumination, make-up or expression are present. However, the 3D shape of the face does not change at all with many of these variations, and changes only minimally with expression. Consequently, an increasing amount of face recognition research is focussing on ways to use the 3D shape of the face for identification.Here, we are proposing to use a Photometric Stereo (PS) method for 3D shape estimation. The main advantages of the proposed method compared to other 3D face shape capture devices will be (1) cheaper to construct hardware, (2) fast acquisition and processing, (3) largely unaffected by ambient illumination, (4) person-specific reflectance considered, (5) more accurate than standard PS, (6) possibility of using the reflectance properties to aid recognition, and (7) minimal calibration required.A large number of methods for using the 3D facial geometry have been proposed in the scientific literature and very promising results have been attained. However, the question of how to capture a subject's 3D face shape prior to recognition is an open one. Existing approaches use technology that is too expensive and too slow for most applications. This proposal is motivated by the need to address this question.The main contributions of the proposed work will be in two areas: photometric stereo (PS) and reflectance analysis. Photometric stereo is a method of estimating the 3D geometry of an object by imaging it under three or more illumination directions. For this project, we will be using five light sources, and aim to simultaneously acquire both shape and reflectance information. We will be using a high speed light-camera synchronisation device developed here at UWE for this task. This will allow deducing a mapping between the orientations of the recovered surface and the measured pixel intensities which will form a quantitative measure of the skin reflectance properties. An iterative method will then be used to update the surface estimate and the reflectance properties until convergence. Thus, we will arrive at a lookup-table set of reflectance measurements and an optimal shape estimate, which will allow for improved face recognition. This is a novel approach to PS and should allow us to diminish some of the strong assumptions on surface orientation that most current methods impose. The main challenge here will be in forming the relationships between the image-based skin reflectance measurements and the skin orientation for the whole face in order to acquire the optimal 3D shape estimate.The final stage of the project will involve applying face recognition methods developed previously both at the MVL and at other institutions for a comparative analysis. This will demonstrate improvements in recognition rates compared to 3D methods using standard PS and other techniques.

The Communications sector is a vital component within the UK economy, with revenues in this area totalling around 129B. Recognised as a key enabler of telecommunications, broadcasting and ICT, communications is also poised to be a transformational technology in areas such as energy, the environment, health and transport. The UK is well placed to reap the full economic and social benefits enabled by communications and investment in a CDT, embracing the breath and reach of the discipline, will help to facilitate our economic recovery and growth and enhance our global standing.There is a serious and growing concern over the future availability of suitably skilled staff to work in the communications sector in the UK. International competition is fierce, with large investments being made by competitor countries in research and in the training of personnel. IT and telecoms companies in the UK are reporting difficulties in attracting candidates with the right skills. In this context, the National Microelectronics Institute and the IET have warned that the ICT sector is facing a growing recruitment crisis with little confidence that the problem will improve in the short or medium term. Various organisations (eg DC-KTN and Royal Academy of Engineering) with support from industry are addressing this issue but acknowledge that it cannot be achieved without relevant high quality under- and postgraduate degrees through which specialist skills can be obtained.To address this shortage, a new Centre for Doctoral Training (CDT) in 'Future Communication' is proposed. The University of Bristol has a world leading reputation in this field, focused on its Centre for Communications Research (CCR), but built on close collaboration between colleagues from Mathematics, Computer Science, Safety Systems and industry. Our vision is to establish a world-leading research partnership which is focused on demand and firmly footed in a commercial context, but with freedom to conduct academically lead blue skies research.The Bristol CDT will be focused on people: not just as research providers, but also as technology consumers and, importantly, as solutions to the UK skills shortage. It will develop the skilled entrepreneurial engineers of the future, provide a coherent advanced training network for the communications community that will be recognised internationally and produce innovative solutions to key emerging research challenges. Over the next eight years, the CDT will build on Bristol's core expertise in Efficient Systems and Enabling Technologies to engineer novel solutions, offering enhanced performance, lower cost and reduced environmental impact. The taught component of the Programme will build on our MSc programme in Communication Systems & Signal Processing, acknowledged as leading in the UK, complemented by additional advanced material in statistics, optimisation and Human-Computer Interaction. This approach will leverage existing commitment and teaching expertise. Enterprise will form a core part of the programme, including: Project Management, Entrepreneurship, Public Communication, Marketing and Research Methods. Through its research programme and some 50 new PhD students, the CDT will undertake fundamental work in communication theory, optimisation and reliability. This will be guided by the commercial imperatives from our industry partners, and motivated by application drivers in Smart Grid, transport, healthcare, military/homeland security, safety critical systems and multimedia delivery. While communications technology is the enabler it is humans that are the consumers, users and beneficiaries in terms of its broader applications. In this respect we will focus our research programme on the challenges within and interactions between the key domains of People, Power and Performance.

We propose to construct a system for 3D face recognition. We propose to use photometric stereo for face reconstruction in order to by pass the problems of conventional stereo (that needs to solve the matching problem first), structured light (that does not supply colour information) and photometric stereo with spectrally distinct light sources (that relies on the assumption of uniformly coloured imaged objects). Photometric stereo (PS) can reproduce structural details and colour on a per pixel basis in a way that no other 3D system can. The proposed scheme will be appropriate for use in a controlled environment for authentication purposes, but also in a general environment e.g. the entrance of a public event. We shall use two routes: surface reconstruction from the data and direct extraction of facial characteristics from the PS set. In the first approach, once surface normal and albedo is recovered, images of the face may be synthetically rendered under arbitrary new pose and illumination conditions to allow novel viewing conditions. We also aim to use a new multi-scale facial feature matching approach in the recognition process, where facial features range from overall face and head shape to fine skin dermal topography, reflectance and texture. The latter may be thought of as a form of detailed surface bump map forming a unique skin-print or signature and represents a new approach. Hence both the 3D shape and 2D intensity data will be used in recognition or authentication tasks. We propose to use scalable methods for matching, so we can cope with large databases. 3D matching will be done with the newly proposed invaders algorithm which is FFT cross-correlation based, and more detailed matching will be done by using features and classifier combination. The novelty of our approach lies in the use of PS to extract 3D information, the use of detailed facial characteristics like moles, scratches, and skin texture, and in the design of the system so that it can operate while the person is moving, with minimum intrusion and maximum efficiency. We have two industrial collaborators who will contribute in system design, data gathering and exploitation and support from the Home Office. We shall evaluate our system following three possible scenaria: a face searched in the crowd (real time face recognition), a person has to be identified (off-line face recognition) and a person has to be checked against a claimed identity (face authentication). We shall install the first prototype system in the offices of one of our industrial partners in month 12, so that data can be collected. We envisage a door like structure with lights flashing in succession as a person walks through, while a camera is capturing images. We propose to investigate the optimal number of lights in terms of efficiency and accuracy of the reconstruction, and the option of using non-visible light to avoid problems with people sensitive to flashes. We shall also investigate the relationship between detail that has to be captured and the geometry of the construction.

As the introduction of automated vehicles becomes feasible, even in urban areas, it will be necessary to investigate their impacts on traffic safety and efficiency. This is particularly true during the early stages of market introduction, where automated vehicles of all SAE levels, connected vehicles (able to communicate via V2X) and conventional vehicles will share the same roads with varying penetration rates. There will be zones and situations on the roads where high automation can be granted, and others where it is not allowed or not possible due to missing sensor inputs, high complexity situations, etc. In the areas where those zones merge many automated vehicles will change their activated level of automation. Therefore, we refer to these areas as “Transition Areas”. TransAID will develop and demonstrate traffic management procedures and protocols to enable smooth coexistence of automated, connected and conventional vehicles especially at Transition Areas. A hierarchical approach will be followed wh