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Beyond the pixels: learning and utilising video compression features for localisation of digital tampering. (2019)
Thesis
JOHNSTON, P. 2019. Beyond the pixels: learning and utilising video compression features for localisation of digital tampering. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Video compression is pervasive in digital society. With rising usage of deep convolutional neural networks (CNNs) in the fields of computer vision, video analysis and video tampering detection, it is important to investigate how patterns invisible to... Read More about Beyond the pixels: learning and utilising video compression features for localisation of digital tampering..

Toward video tampering exposure: inferring compression parameters from pixels. (2018)
Presentation / Conference Contribution
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Proceedings of the 19th International conference on engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. Communications in computer and information science, 893. Cham: Springer [online], pages 44-57, Available from: https://doi.org/10.1007/978-3-319-98204-5_4

Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression of the complete stream. Rec... Read More about Toward video tampering exposure: inferring compression parameters from pixels..