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Publication - Dr Tilo Burghardt

    DeepKey

    Towards End-to-End Physical Key Replication From a Single Photograph

    Citation

    Smith, R & Burghardt, T, 2018, ‘DeepKey: Towards End-to-End Physical Key Replication From a Single Photograph’. in: Proceedings of the 40th German Conference on Pattern Recognition (GCPR), October 2018.. Springer, Cham

    Abstract

    This paper describes DeepKey, an end-to-end deep neural architecture capable of taking a digital RGB image of an ‘everyday’ scene containing a pin tumbler key (e.g. lying on a table or carpet) and fully automatically inferring a printable 3D key model. We report on the key detection performance and describe how candidates can be transformed into physical prints. We show an example opening a real-world lock. Our system is described in detail, providing a breakdown of all components including key detection, pose normalisation, bitting segmentation and 3D model inference. We provide an in-depth evaluation and conclude by reflecting on limitations, applications, potential security risks and societal impact. We contribute the DeepKey Datasets of 5,300+ images covering a few test keys with bounding boxes, pose and unaligned mask data.

    Full details in the University publications repository