Abstract: Cameras are widely deployed in public and professional environments,but their functionality is limited to capturing video images.When ranging is required,binocular cameras or other ranging devices need to be installed.Taking the decentralized cameras already installed in substations as an example,this paper proposes a collaborative ranging method based on decentralized multi-view visual baselines.By dynamically constructing multiple sets of virtual binocular pairs,the method enables ranging for moving targets without additional hardware.Utilizing existing high-definition cameras with known pose parameters and reference objects,the proposed approach dynamically establishes binocular baselines and integrates spatiotemporal consistency across multiple views to achieve real-time target localization and safety ranging.The research content includes:self-calibration and baseline optimization mechanism for multi-camera pose parameters,depth estimation of moving targets based on binocular geometric constraints,target keypoint matching strategy integrating semantic segmentation,and weighted fusion algorithm for multi-baseline collaborative ranging.Experimental results in laboratory and real substation scenarios show that the proposed method can achieve centimeter-level ranging accuracy on low-computing-power edge devices,significantly out performing traditional single-baseline binocular systems.It offers high engineering applicability and promotional value.

Key words: Decentralized cameras, Binocular ranging, Multi-baseline coordination, Moving target localization