朱海红, 温雅, 毛凯, 李霖, 李国忠, 李宇琪. 室内地标提取的POI显著度定量评价模型[J]. 武汉大学学报 ( 信息科学版), 2018, 43(3): 336-341. DOI: 10.13203/j.whugis20150149
引用本文: 朱海红, 温雅, 毛凯, 李霖, 李国忠, 李宇琪. 室内地标提取的POI显著度定量评价模型[J]. 武汉大学学报 ( 信息科学版), 2018, 43(3): 336-341. DOI: 10.13203/j.whugis20150149
ZHU Haihong, WEN Ya, MAO Kai, LI Lin, LI Guozhong, LI Yuqi. A Quantitative POI Salience Model for Indoor Landmark Extraction[J]. Geomatics and Information Science of Wuhan University, 2018, 43(3): 336-341. DOI: 10.13203/j.whugis20150149
Citation: ZHU Haihong, WEN Ya, MAO Kai, LI Lin, LI Guozhong, LI Yuqi. A Quantitative POI Salience Model for Indoor Landmark Extraction[J]. Geomatics and Information Science of Wuhan University, 2018, 43(3): 336-341. DOI: 10.13203/j.whugis20150149

室内地标提取的POI显著度定量评价模型

A Quantitative POI Salience Model for Indoor Landmark Extraction

  • 摘要: 室内地标在室内位置信息服务(location based service,LBS)中发挥着重要作用。针对室外地标提取方法不能完全适用于更为复杂的室内环境的问题,提出了一种显著度定量评价模型用于在室内环境中提取地标。以大型商场的室内环境为研究对象,从视觉、认知、空间3个方面分析影响室内兴趣点(point of interest,POI)显著性的主要因素,并用这些因素构建了室内POI整体显著度评价模型。选择武汉市群光购物中心室内的POI数据进行显著度计算,依据显著度的差异性提取了多层地标,反映不同粒度的室内区域空间知识。提取的多层地标可以作为室内智能导航系统中的重要标识,为在复杂的大型商场内实现快速寻路、多粒度路径导引提供关键线索。

     

    Abstract: Indoor landmarks play an important role in the location-based service (LBS). On account of outdoor landmark extraction methods can not be fully applicable to complex indoor environment, we propose a suitable indoor landmark saliency quantitative evaluation model to extract indoor landmarks. In this paper, large shopping malls are regarded as research site, after analyzing the factors influencing the saliency of POI objects from perceptual, cognitive and spatial structure, a saliency measure model composed of these factors is constructed. Finally, we compute the significances of the POIs selected from the interior of Chicony shopping mall of Wuhan city. In this experiment, several level of landmarks are extracted to reflect different size of spatial knowledge in indoor spaces. Extracted indoor landmarks can be important symbols in indoor intelligent navigation system and as key clues in a large shopping malls wayfinding, multi-granularity route directions.

     

/

返回文章
返回