Abstract

In this work, models for re-identification of pedestrians, based on deep learning, are studied. The models considered here use only images of pedestrians and do not require additional spatiotemporal information that can vary in different instances. A modification of the investigated models is proposed, based on the normalization of feature maps. In the best case, an assessment of the accuracy of the model demonstrates a 10% improvement over unmodified models.

© 2020 Optical Society of America

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