Passenger and pedestrian recognition based on neural networks and deep learning in stations

Zhiyuan Zhang

doi:10.1117/12.2672158

16 March 2023 Passenger and pedestrian recognition based on neural networks and deep learning in stations

Zhiyuan Zhang

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 1259315 (2023) https://doi.org/10.1117/12.2672158
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

Pedestrian detection technology has high application value in various fields, and deep learning has become a key development direction in computer vision. Human object detection has also shifted from traditional detection algorithms to deep learning. Due to the influence of complex light and obstacles in the station, as well as the occlusions and size changes of passengers, the algorithm must be optimized for these complex scenes. This paper takes pedestrian detection technology as the goal, compares the methods based on human body parts recognition from the concepts and classification of artificial neural networks and deep learning, and profoundly discusses the convolutional neural network based on deep learning. Finally, pedestrian detection algorithms' problems and future trends are compared and discussed.

Citation Download Citation

Zhiyuan Zhang "Passenger and pedestrian recognition based on neural networks and deep learning in stations", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 1259315 (16 March 2023); https://doi.org/10.1117/12.2672158

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