Original title: Realtime Pedestrian Recognition Using Siamese Network
Authors: Rajnoha, Martin
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Image similarity measuring has many various applications. Pedestrian recognition is one of them and for the security purposes it is basically required to run in real-time. This paper proposes a deep Siamese neural network architecture for pedestrian recognition that achieves 70.28% accuracy on the test set containing 20 persons. Prediction of the model is fast enough for real-time processing.
Keywords: deep learning; pedestrian; recognition; Siamese; surveillance
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/138273

Permalink: http://www.nusl.cz/ntk/nusl-393459


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers