UKHO Celestial Navigation Project

The research questions:

The project will look to utilise imagery of the night sky to perform prediction of the cameras position. The key research questions for the project include whether imagery of the night sky can be used by a machine learning system to regress camera coordinates and parameters. The project will also look into underlying methods which allow feature extraction and generalisation in order to adequately train a reliable and accurate regression model. Exploration into the impact of noise into the system will also be explored, evaluating the impact when certain bodies may not be visible to the camera or when light pollution is introduced.



The approaches used:

The project will utilise an unsupervised approach to identifying the key celestial bodies in an image, extracting the keypoints from an image to provide an observation into the night sky. Conventional image processing and machine learning methods will be used to detect the keypoints. These keypoints will then be used to regress the camera pose parameters by training a model on labelled samples. Evaluation of model robustness to noise will also be explored, given parameters such as light pollution and occlusion. This will then be used to produce interpretable representations of the prediction for the user, by observing the importance each body contributes to the prediction in an intuitive visualisation.



Novel content:

Besides the improvement in camera regression ability, the project novelty comes from the application domain, and the use of a human-centred approach to interpretable prediction visualisation. The interpretation of the results is key when developing a navigational system that utilises machine learning, allowing for predictions to be scrutinised by the domain expert. The development of methods robust to occlusion of stars in the image is also a key contribution.

The Centre will nurture 55 new PhD researchers who will be highly sought after in technology companies and application sectors where data and intelligence based systems are being developed and deployed. We expect that our graduates will be nationally in demand for two reasons: firstly, their training occurs in a vibrant and unique environment exposing them to challenging domains and contexts (that provide stretch, ambition and adventure to their projects and capabilities); and, secondly, because of the particular emphasis the Centre will put on people-first approaches. As one of the Google AI leads, Fei-Fei Li, recently put it, "We also want to make technology that makes humans' lives better, our world safer, our lives more productive and better. All this requires a layer of human-level communication and collaboration" [1]. We also expect substantial and attractive opportunities for the CDT's graduates to establish their careers in the Internet Coast region (Swansea Bay City Deal) and Wales. This demand will dovetail well with the lifetime of the Centre and provide momentum for its continuation after the initial EPSRC investment.

With the skills being honed in the Centre, the UK will gain a important competitive advantage which will be a strong talent based-pull, drawing in industrial investment to the UK as the recognition of and demand for human-centred interactions and collaborations with data and intelligence multiplies. Further, those graduates who wish to develop their careers in the academy will be a distinct and needed complement to the likely increased UK community of researchers in AI and big data, bringing both an ability to lead insights and innovation in core computer science (e.g., in HCI or formal methods) allied to talents to shape and challenge their research agenda through a lens that is human-centred and that involves cross-disciplinarity and co-creation.

The PhD training will be the responsibility of a team which includes research leaders in the application of big data and AI in important UK growth sectors - from health and well being to smart manufacturing - that will help the nation achieve a positive and productive economy. Our graduates will tackle impactful challenges during their training and be ready to contribute to nationally important areas from the moment they begin the next steps of their careers. Impact will be further embedded in the training programme with cohorts involved in projects that directly involve communities and stakeholders within our rich innovation ecology in Swansea and the Bay region who will co-create research and participate in deployments, trials and evaluations.

The Centre will also impact by providing evidence of and methods for integrating human-centred approaches within areas of computational science and engineering that have yet to fully exploit their value: for example, while process modelling and verification might seem much removed from the human interface, we will adapt and apply methods from human-computer interaction, one of our Centre's strengths, to develop research questions, prototyping apparatus and evaluations for such specialisms. These valuable new methodologies, embodied in our graduates, will impact on the processes adopted by a wide range of organisations we engage with and who our graduates join.

Finally, as our work is fully focused on putting the human first in big data and intelligent systems contexts, we expect to make a positive contribution to society's understandings of and involvement with these keystone technologies. We hope to reassure, encourage and empower our fellow citizens, and those globally, that in a world of "smart" technology, the most important ingredient is the human experience in all its smartness, glory, despair, joy and even mundanity.

[1] https://www.technologyreview.com/s/609060/put-humans-at-the-center-of-ai/