Chintakindi Balaram Murthy1, Mohammad Farukh Hashmi1, Ghulam Muhammad2,3,*, Salman A. AlQahtani2,3
CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3015-3031, 2021, DOI:10.32604/cmc.2021.018781
Abstract Real-time pedestrian detection is an important task for unmanned driving systems and video surveillance. The existing pedestrian detection methods often work at low speed and also fail to detect smaller and densely distributed pedestrians by losing some of their detection accuracy in such cases. Therefore, the proposed algorithm YOLOv2 (“YOU ONLY LOOK ONCE Version 2”)-based pedestrian detection (referred to as YOLOv2PD) would be more suitable for detecting smaller and densely distributed pedestrians in real-time complex road scenes. The proposed YOLOv2PD algorithm adopts a Multi-layer Feature Fusion (MLFF) strategy, which helps to improve the model’s feature extraction ability. In addition, one… More >
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