Abstract: Deep learning and computer vision play an important role and is of great value in industrial upgrading; they are key technologies for constructing next-generation intelligent library. Pedestrian detection is an important research and application direction of this field. This work explores the application of pedestrian detection method to library for the first time, and discusses the important value
of the related applications in detail based on some real examples. The authors create the pedestrian detection representative method – YOLOv3 on open pedestrian databases, and successfully deploy the detection system in NWPU library. Some representative scenarios show that YOLOv3 can satisfy library needs both in terms of accuracy and of run-time performance. This work is a valuable attempt of applying
deep learning and computer vision technology in smart library field, and has good reference for utilizing related technologies in library.