High Performance Embedded and Distributed Systems (HiPEDS), ranging from implantable smart sensors to secure cloud service providers, offer exciting benefits to society and great opportunities for wealth creation. Although currently UK is the world leader for many technologies underpinning such systems, there is a major threat which comes from the need not only to develop good solutions for sharply focused problems, but also to embed such solutions into complex systems with many diverse aspects, such as power minimisation, performance optimisation, digital and analogue circuitry, security, dependability, analysis and verification. The narrow focus of conventional UK PhD programmes cannot bridge the skills gap that would address this threat to the UK's leadership of HiPEDS. The proposed Centre for Doctoral Training (CDT) aims to train a new generation of leaders with a systems perspective who can transform research and industry involving HiPEDS. The CDT provides a structured and vibrant training programme to train PhD students to gain expertise in a broad range of system issues, to integrate and innovate across multiple layers of the system development stack, to maximise the impact of their work, and to acquire creativity, communication, and entrepreneurial skills. The taught programme comprises a series of modules that combine technical training with group projects addressing team skills and system integration issues. Additional courses and events are designed to cover students' personal development and career needs. Such a comprehensive programme is based on aligning the research-oriented elements of the training programme, an industrial internship, and rigorous doctoral research. Our focus in this CDT is on applying two cross-layer research themes: design and optimisation, and analysis and verification, to three key application areas: healthcare systems, smart cities, and the information society. Healthcare systems cover implantable and wearable sensors and their operation as an on-body system, interactions with hospital and primary care systems and medical personnel, and medical imaging and robotic surgery systems. Smart cities cover infrastructure monitoring and actuation components, including smart utilities and smart grid at unprecedented scales. Information society covers technologies for extracting, processing and distributing information for societal benefits; they include many-core and reconfigurable systems targeting a wide range of applications, from vision-based domestic appliances to public and private cloud systems for finance, social networking, and various web services. Graduates from this CDT will be aware of the challenges faced by industry and their impact. Through their broad and deep training, they will be able to address the disconnect between research prototypes and production environments, evaluate research results in realistic situations, assess design tradeoffs based on both practical constraints and theoretical models, and provide rapid translation of promising ideas into production environments. They will have the appropriate systems perspective as well as the vision and skills to become leaders in their field, capable of world-class research and its exploitation to become a global commercial success.

We propose to develop methodologies for automatic construction of person-specific facial deformable models for robust tracking of facial motion in unconstrained videos (recorded 'in-the-wild'). The tools are expected to work well for data recorded by a device as cheap as a web-cam and in almost arbitrary recording conditions. The technology that will be developed in the project is expected to have a huge impact in many different applications including but not limited to, biometrics (face recognition), Human Computer Interaction (HCI) systems, as well as, analysis and indexing of videos using facial information (e.g., YouTube), capturing of facial motion in games and film industry, creating virtual avatars, just to name a few. The novelty of the ADAMant technology is multi-faceted. We propose the very first, robust, discriminative deformable facial models that can be customized, in an incremental fashion, so that they can automatically tailor themselves to the person's face using image sequences under uncontrolled recording conditions (both indoors and outdoors). Also, we propose to build and publicly release the first annotated, with regards to facial landmarks, database of facial videos made 'in-the-wild'. Finally, we aim to use the database as the base of the first competition for facial landmark tracking 'in-the-wild', which will run as a satellite workshop of a top vision venue (such as ICCV 2015). As a proof of concept, and with a focus on a novel application, the ADAMant technology will be applied for (1) facial landmark tracking for machine analysis of behaviour in response to product adverts watched by people at comfort of their home (indoors) and (2) facial landmark tracking for automatic face verification using videos recorded by mobile devices (outdoors). In an increasingly global economy and ever-ubiquitous digital age, the market can change rapidly. As stipulated by the UK Researcher Councils' Digital Economy Theme, realising substantial transformational impact on how new business models are being created and taking advantage of the digital world is one of the main challenges. As human face is at the heart of many scientific disciplines and business models, the ADAManT project provides technology that can reshape established business models to become more efficient but also create new ones. Within EPSRC's ICT priorities our research is extremely relevant to autonomous systems and robotics, since it enables the development of robots capable of understanding human behaviour in unconstrained environments (i.e., design of robot companions, robots as tourist guide, etc.).