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The Video Collaborative Localization of a Miner’s Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines

Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several...

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Detalles Bibliográficos
Autores principales: You, Kaiming, Yang, Wei, Han, Ruisong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634448/
https://www.ncbi.nlm.nih.gov/pubmed/26426023
http://dx.doi.org/10.3390/s151025103
Descripción
Sumario:Based on wireless multimedia sensor networks (WMSNs) deployed in an underground coal mine, a miner’s lamp video collaborative localization algorithm was proposed to locate miners in the scene of insufficient illumination and bifurcated structures of underground tunnels. In bifurcation area, several camera nodes are deployed along the longitudinal direction of tunnels, forming a collaborative cluster in wireless way to monitor and locate miners in underground tunnels. Cap-lamps are regarded as the feature of miners in the scene of insufficient illumination of underground tunnels, which means that miners can be identified by detecting their cap-lamps. A miner’s lamp will project mapping points on the imaging plane of collaborative cameras and the coordinates of mapping points are calculated by collaborative cameras. Then, multiple straight lines between the positions of collaborative cameras and their corresponding mapping points are established. To find the three-dimension (3D) coordinate location of the miner’s lamp a least square method is proposed to get the optimal intersection of the multiple straight lines. Tests were carried out both in a corridor and a realistic scenario of underground tunnel, which show that the proposed miner’s lamp video collaborative localization algorithm has good effectiveness, robustness and localization accuracy in real world conditions of underground tunnels.