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RESEARCH ON SEMANTIC MAP GENERATION AND LOCATION INTELLIGENT RECOGNITION METHOD FOR SCENIC SPOT SPACE PERCEPTION

机译:语义地图生成与定位智能识别方法对景区空间感知的研究

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In recent years, Tourism has become more and more Chinese leisure travel choice The research on the smart scenic spot is getting deeper and deeper, but the problem of accurate location l in the natural scenic spot still needs to be solved. Semantic maps contain a wealth of environmental information and can be more efficient for location-aware services, and are attracting more and more attention from researchers at home and abroad. In order to better ensure the travel experience of tourists, the range of scenic spots is too large, and the signal interference is high. Complex terrain in the scenic area, Branch and leaf features Visitors cannot rely on traditional positioning systems to get their current accurate location. It is proposed to construct a navigation semantic map for the perception of scenic space. In the construction process, the operation based on the location perception of the tourists and the surrounding environment and the extraction of the feature information is the key to constructing the semantic map. The general image recognition method is used to obtain the environment image information, and the acquired feature image is recognized to obtain the semantic information in the environment; in order to obtain more feature environment information to better complete the location-aware service task, the GBP descriptor is used. The method divides and stores different semantic regions in the environment, and generates a semantic map with rich semantic information and feature information according to the three-dimensional map model.
机译:近年来,旅游业已成为越来越多的中国休闲旅游选择,智能景区的研究正在越来越深,而且需要解决自然风景区中的准确位置l的问题。语义地图包含丰富的环境信息,可以更高效地用于定位服务,并在国内外的研究人员吸引越来越多的关注。为了更好地确保游客的旅行体验,景点范围太大,信号干扰很高。在风景区,分支机构的复杂地形,分支和叶子的特色游客不能依靠传统的定位系统来获得当前的准确位置。建议构建一个导航语义地图,以了解景区空间的感知。在施工过程中,基于游客和周围环境的位置感知的操作以及特征信息的提取是构建语义地图的关键。通用图像识别方法用于获得环境图像信息,并且识别所获取的特征图像以获得环境中的语义信息;为了获得更多特征环境信息以更好地完成位置感知服务任务,使用GBP描述符。该方法在环境中划分和存储不同的语义区域,并根据三维地图模型生成具有丰富语义信息和特征信息的语义图。

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