Realtime Pedestrian Recognition Using Siamese Network
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