H-Unique: In Search of Uniqueness
Harnessing Anatomical Hand Variation
H-unique is a five year, €2.5m programme of research that will be the first multimodal automated interrogation of visible hand anatomy, through analysis and interpretation of human variation via images. It is an interdisciplinary project, supported by anatomists, anthropologists, geneticists, bioinformaticians, image analysts and computer scientists.
We will investigate the inherent and acquired variation in search of uniqueness, as the hand retains and displays a multiplicity of anatomical variants formed by different aetiologies (genetics, development, environment, accident etc). The project has arisen directly from Prof. Black’s ground-breaking research in relation to the forensic identification of individuals from images of their anatomy in child abuse cases.
The hand retains and displays many anatomical differences due to our genetics, development, environment or even accidents so each person’s hands are different. Now for the first time, researchers will analyse all the factors that make a hand truly unique so we can understand and use them reliably as evidence to identify individuals.
Prof Dame Sue Black, Baroness of Strome
How you can contribute
To help with this research we are appealing for 5,000 ‘citizen scientists’ to anonymously complete a short questionnaire and contribute images to the world’s first searchable database of the anatomy and variations of the human hand.
For more information on what data we will be capturing and how it will be used, please read the participant information
As our preferred contribution method, we have developed a simple web application through which anybody over the age of 18 can contribute data to the project using a smartphone with a standard web browser and camera.
If you are viewing this page on a mobile phone browser, please click the contribute link below to start the contribution app.
If you are viewing this page on a laptop or desktop machine, please open this page in your phone browser or scan this QR code with your mobile phone.
For those that are unable to contribute using a smart phone, we can also accept contributions via e-mail. Please click here for details of E-mail contribution.
Register Interest
You can also register with our mailing list to receive progress updates during the life of the project.
News
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Weakly Supervised Co-training with Swapping Assignments for Semantic Segmentation
Yang X, Rahmani H, Black S, Williams BM. arXiv preprint arXiv:2402.17891. 2024 Feb 27.
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Sustainability
Artificial intelligence (AI) has a crucial role to play in the future of sustainability, with unprecedented ability to process, analyse and interpret large datasets, driving innovation in many areas including health, waste management and resource optimization. Our Imaging and Computer Vision Lancaster (iCVL) research group is focused on developing world-leading […]
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A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image
Jiang Z, Rahmani H, Black S, Williams BM. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 (pp. 758-767).
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VACANCY: Senior Research Associate/Research Associate in Image Processing, Computer Vision and Machine Learning (H-unique)
We have 2 (Senior) Research Associate positions in Image Processing, Computer Vision and Machine Learning available, based on the School of Computing and Communications, Lancaster University. Salary: £36,386 to £42,155Closing Date: Friday 14 October 2022Interview Date: Friday 21 October 2022Reference: 0994-22 This is an opportunity to join our Imaging and […]
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Graph-context Attention Networks for Size-varied Deep Graph Matching
Jiang Z, Rahmani H, Angelov P, Black S, Williams BM. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022 (pp. 2343-2352).
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Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning
Baisa NL, Williams B, Rahmani H, Angelov P, Black S. In 2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA) 2022 Apr 19 (pp. 1-6). IEEE.
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ERC: What Makes our Hands Unique?
Whereas fingerprint analysis is widely used in forensic science, the rest of our hands equally retains a wealth of anatomical information. Bringing together anatomy and biometrics, ERC grantee Sue Black seeks to understand variability in the human hand though images contributed by ‘citizen scientists’. In search of uniqueness, she uses […]
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