Spatio-temporal perception of tourists in mountainous scenic areas using distributed camera networks proximal sensing

doi:10.13474/j.cnki.11-2246.2025.0112

Abstract

Abstract: Mountainous scenic areas rely on distributed camera networks for real-time visitor perception, a crucial aspect of intelligent scenic area development. This paper exploits these networks to propose a method for dynamic and precise passive perception of visitors in mountainous scenic areas through distributed cameras. By enhancing the YOLOX network with a convolutional block attention module (CBAM) and adaptive spatial feature fusion (ASFF) techniques, and incorporating a dynamic target tracking algorithm, this method achieves accurate detection and tracking of visitors' movements. Subsequently, a localization algorithm is utilized to derive real-time positional information of visitors. The results demonstrate the method's effectiveness in near-field passive perception and spatial positioning within mountainous scenic areas, achieving a detection precision over 90%, spatial positioning accuracy within 1 m, and a root mean square error (RMSE) of less than 1.109 4. This provides a technical solution and information support for the passive real-time dynamic precise perception and safety management of visitors in areas with weak or no satellite navigation signals.

Key words: object detection, near-field perception, spatio-temporal distribution, dynamic management, mountainous scenic areas

CLC Number:

P237

SHI Kuntao, ZHU Changming, ZHANG Xin, YANG Fan, ZHANG Kun, GAO Hongjin. Spatio-temporal perception of tourists in mountainous scenic areas using distributed camera networks proximal sensing[J]. Bulletin of Surveying and Mapping, 2025, 0(1): 72-77.

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