Realtime Pedestrian Recognition Using Siamese Network
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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.
Document typePeer reviewed
Document versionFinal PDF
SourceProceedings of the 24th Conference STUDENT EEICT 2018. s. 441-445. ISBN 978-80-214-5614-3
- Student EEICT 2018