A Multi-Scale Representation of Point-of-Interest (POI) Features in Indoor Map Visualization

As a result of the increasing popularity of indoor activities, many facilities and services are provided inside buildings; hence, there is a need to visualize points-of-interest (POIs) that can describe these indoor service facilities on indoor maps. Over the last few years, indoor mapping has been a rapidly developing area, with the emergence of many forms of indoor representation. In the design of indoor map applications, cartographical methodologies such as generalization and symbolization can make important contributions. In this study, a self-adaptive method is applied for the design of a multi-scale and personalized indoor map. Based on methods of map generalization and multi-scale representation, we adopt a scale-adaptive strategy to visualize the building structure and POI data on indoor maps. At smaller map scales, the general floor distribution and functional partitioning of each floor are represented, while the POI data are visualized by simple symbols. At larger map scales, the detailed room distribution is displayed, and the service information of the POIs is described by detailed symbols. Different strategies are used for the generalization of the background building structure and the foreground POI data to ensure that both can satisfy real-time performance requirements. In addition, for better personalization, different POI data, symbols or color schemes are shown to users in different age groups, with different genders or with different purposes for using the map. Because this indoor map is adaptive to both the scale and the user, each map scale can provide different map users with decision support from different perspectives.

[1]  Qing Zhu,et al.  Problems in indoor mapping and modelling , 2013 .

[2]  J. Chen DEFINING SEMANTIC LEVELS OF DETAIL FOR INDOOR MAPS , 2018, SDSC 2018.

[3]  Thomas H. Kolbe,et al.  Map design aspects, route complexity, or social background? Factors influencing user satisfaction with indoor navigation maps , 2013 .

[4]  Tinghua Ai,et al.  An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China , 2017 .

[5]  Qingyun Du,et al.  Web map-based POI visualization for spatial decision support , 2013 .

[6]  Alexander Salveson Nossum IndoorTubes A Novel Design for Indoor Maps , 2011 .

[7]  Chi Zhang,et al.  Generation of navigation networks for corridor spaces based on indoor visibility map , 2019, Int. J. Geogr. Inf. Sci..

[8]  Xiang Zhang,et al.  A vector field model to handle the displacement of multiple conflicts in building generalization , 2015, Int. J. Geogr. Inf. Sci..

[9]  Jun Chen,et al.  Automated building generalization based on urban morphology and Gestalt theory , 2004, Int. J. Geogr. Inf. Sci..

[10]  Monika Sester,et al.  Optimization approaches for generalization and data abstraction , 2005, Int. J. Geogr. Inf. Sci..

[11]  Filip Biljecki,et al.  Proposal for a new LOD and multi-representation concept for CityGML , 2016 .

[12]  Sisi Zlatanova,et al.  A BIM-Oriented Model for supporting indoor navigation requirements , 2013, Comput. Environ. Urban Syst..

[13]  Yuan Lei,et al.  A Full Level-of-Detail Specification for 3D Building Models Combining Indoor and Outdoor Scenes , 2018, ISPRS Int. J. Geo Inf..

[14]  Wei Yang,et al.  POI Information Enhancement Using Crowdsourcing Vehicle Trace Data and Social Media Data: A Case Study of Gas Station , 2018, ISPRS Int. J. Geo Inf..

[15]  Xiangyu Wang,et al.  A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level , 2018, ISPRS Int. J. Geo Inf..

[16]  Yifan Zhang,et al.  Automated Generalization of Facility Points-of-Interest With Service Area Delimitation , 2019, IEEE Access.

[17]  Xiangyu Wang,et al.  A State-of-the-Art Review on the Integration of Building Information Modeling (BIM) and Geographic Information System (GIS) , 2017, ISPRS Int. J. Geo Inf..

[18]  Adam C. Winstanley,et al.  Indoor location based services challenges, requirements and usability of current solutions , 2017, Comput. Sci. Rev..

[19]  Jingzhong Li,et al.  Envelope generation and simplification of polylines using Delaunay triangulation , 2017, Int. J. Geogr. Inf. Sci..

[20]  Chimay J. Anumba,et al.  A framework for 3D traffic noise mapping using data from BIM and GIS integration , 2016 .

[21]  Lu Wang,et al.  A new approach to simplifying polygonal and linear features using superpixel segmentation , 2018, Int. J. Geogr. Inf. Sci..

[22]  Jean-Claude Thill,et al.  Enhanced 3D visualization techniques in support of indoor location planning , 2015, Comput. Environ. Urban Syst..

[23]  Jacek Marciniak,et al.  Cartographical Aspects in the Design of Indoor Navigation Systems , 2012 .

[24]  Alexander Salveson Nossum,et al.  Developing a Framework for Describing and Comparing Indoor Maps , 2013 .

[25]  Kiwon Lee,et al.  Handling Points of Interest (POIs) on a Mobile Web Map Service Linked to Indoor Geospatial Objects: A Case Study , 2018, ISPRS Int. J. Geo Inf..