Due to recent progress of geospatial and mobile technologies, it becomes available to provide geospatial information services to visually impaired people such as BlindSquare. In this demo paper, we present a prototype of voice indoor routing map service, called VIM(Voice-based Indoor Maps) for visually impaired people. This prototype service has been designed for navigation along braille blocks between two points in indoor space and developed by using TalkBack user-interface of Android OS. The voice navigation information is mainly based on an OGC standard [3], IndoorGML [2], which serves as the framework data model and XML schema to describe the network connectivity in indoor space. The data model of VIM is designed by considering several safety requirements for visually impaired people. The prototype service has been implemented and tested on a real site of subway station in Seoul.
{"title":"Indoor navigation map for visually impaired people","authors":"Hyeong-Gyu Ryu, Taehoon Kim, Ki-Joune Li","doi":"10.1145/2676528.2676533","DOIUrl":"https://doi.org/10.1145/2676528.2676533","url":null,"abstract":"Due to recent progress of geospatial and mobile technologies, it becomes available to provide geospatial information services to visually impaired people such as BlindSquare. In this demo paper, we present a prototype of voice indoor routing map service, called VIM(Voice-based Indoor Maps) for visually impaired people. This prototype service has been designed for navigation along braille blocks between two points in indoor space and developed by using TalkBack user-interface of Android OS. The voice navigation information is mainly based on an OGC standard [3], IndoorGML [2], which serves as the framework data model and XML schema to describe the network connectivity in indoor space. The data model of VIM is designed by considering several safety requirements for visually impaired people. The prototype service has been implemented and tested on a real site of subway station in Seoul.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127751243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Indoor navigation applications for mobile devices are being more common and needed for people who want to find inside building destinations. Many indoor navigation applications utilize different technologies, such as Wi-Fi fingerprinting, have been suggested. Most of these applications use a fixed background map and pre-calculated paths to lead the user to their destinations. Users of these systems need general map reading skills and understanding how specifically indoor maps work. In addition, these system types need to implement complex and accurate calculations to determine routing paths before navigation starts - which could be affected by unstable Wi-Fi signals. In this paper, we suggest INSAR or Indoor Navigation System Using Augmented Reality, which utilizes Wi-Fi fingerprinting, augmented reality (AR), and digital compass technologies in an integrated Android-based app. Specifically, we used a Wi-Fi fingerprinting method to determine user position, augmented reality to display real-time navigation information, and a compass to determine destination direction. Additionally, digital compass use to read the destination direction of each reference point (RP) helps direct the users "on the fly" thus reducing potential Wi-Fi signal instability effects.
{"title":"INSAR: indoor navigation system using augmented reality","authors":"Ahmed Alnabhan, Brian M. Tomaszewski","doi":"10.1145/2676528.2676535","DOIUrl":"https://doi.org/10.1145/2676528.2676535","url":null,"abstract":"Indoor navigation applications for mobile devices are being more common and needed for people who want to find inside building destinations. Many indoor navigation applications utilize different technologies, such as Wi-Fi fingerprinting, have been suggested. Most of these applications use a fixed background map and pre-calculated paths to lead the user to their destinations. Users of these systems need general map reading skills and understanding how specifically indoor maps work. In addition, these system types need to implement complex and accurate calculations to determine routing paths before navigation starts - which could be affected by unstable Wi-Fi signals. In this paper, we suggest INSAR or Indoor Navigation System Using Augmented Reality, which utilizes Wi-Fi fingerprinting, augmented reality (AR), and digital compass technologies in an integrated Android-based app. Specifically, we used a Wi-Fi fingerprinting method to determine user position, augmented reality to display real-time navigation information, and a compass to determine destination direction. Additionally, digital compass use to read the destination direction of each reference point (RP) helps direct the users \"on the fly\" thus reducing potential Wi-Fi signal instability effects.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"27 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120915987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Humans spend most of their life in indoor spaces. As indoor spaces are becoming increasingly complex, there are compelling needs for efficient indoor GIS and navigation systems. For indoor navigations, numerous geometric network models have been proposed as navigable spatial models for 3D indoor environments in the past decade. Most of the existing discussions, however, tend to focus on conceptual representations of geometric networks; not enough attention has been given on the generation processes of navigable networks for 3D indoor environments. It is actually nontrivial, considering accurate and complete floor plans, the conventional data sources for building indoor geometric networks, are oftentimes not available for various reasons (e.g., copyright, public safety concerns). With the continue advances of 3D imaging and scanning technologies, 3D data models with fine geometric structures and high quality textures are increasingly available for indoor spaces, thus provide a novel data source for building indoor geometric networks. In this paper, an interactive approach is presented to derive 3D, navigable, geometric network models from these 3D data models. Specifically, this approach includes three steps: decomposing 3D building models in terms of floors, interactively creating geometric network elements (e.g., nodes and edges) and then automatically generating geometric network models. The presented approach is implemented and its advantages are demonstrated with a real world 3D building data.
{"title":"An interactive approach for deriving geometric network models in 3D indoor environments","authors":"Feixiong Luo, G. Cao, Xiang Li","doi":"10.1145/2676528.2676531","DOIUrl":"https://doi.org/10.1145/2676528.2676531","url":null,"abstract":"Humans spend most of their life in indoor spaces. As indoor spaces are becoming increasingly complex, there are compelling needs for efficient indoor GIS and navigation systems. For indoor navigations, numerous geometric network models have been proposed as navigable spatial models for 3D indoor environments in the past decade. Most of the existing discussions, however, tend to focus on conceptual representations of geometric networks; not enough attention has been given on the generation processes of navigable networks for 3D indoor environments. It is actually nontrivial, considering accurate and complete floor plans, the conventional data sources for building indoor geometric networks, are oftentimes not available for various reasons (e.g., copyright, public safety concerns). With the continue advances of 3D imaging and scanning technologies, 3D data models with fine geometric structures and high quality textures are increasingly available for indoor spaces, thus provide a novel data source for building indoor geometric networks. In this paper, an interactive approach is presented to derive 3D, navigable, geometric network models from these 3D data models. Specifically, this approach includes three steps: decomposing 3D building models in terms of floors, interactively creating geometric network elements (e.g., nodes and edges) and then automatically generating geometric network models. The presented approach is implemented and its advantages are demonstrated with a real world 3D building data.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125508192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics which concerns mapping an environment or space while simultaneously localizing within this map. Given that one of the major goals of robotics is to perform tasks commonly performed by humans, we argue that SLAM methods should be cognitively adequate; that is, they should model the same properties of a space as the human cognition models. Topological properties are considered the most fundamental of those modelled by the human cognition. Therefore in order to achieve cognitive adequacy such properties must be modelled explicitly. Research in the domain of spatial cognition has demonstrated that the topological properties modelled by the human cognition can be quantified using the Egenhofer Nine-Intersection Model (9-IM). In this work we propose a conceptual SLAM method which models the same properties as the 9-IM. Relative to existing topological SLAM methods, which model a single topological property of connectivity between locations, this method achieves a stronger degree of cognitive adequacy.
{"title":"Cognitively adequate topological robot localization and mapping","authors":"P. Corcoran, M. Bertolotto, J. Leonard","doi":"10.1145/2676528.2676534","DOIUrl":"https://doi.org/10.1145/2676528.2676534","url":null,"abstract":"Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics which concerns mapping an environment or space while simultaneously localizing within this map. Given that one of the major goals of robotics is to perform tasks commonly performed by humans, we argue that SLAM methods should be cognitively adequate; that is, they should model the same properties of a space as the human cognition models. Topological properties are considered the most fundamental of those modelled by the human cognition. Therefore in order to achieve cognitive adequacy such properties must be modelled explicitly. Research in the domain of spatial cognition has demonstrated that the topological properties modelled by the human cognition can be quantified using the Egenhofer Nine-Intersection Model (9-IM). In this work we propose a conceptual SLAM method which models the same properties as the 9-IM. Relative to existing topological SLAM methods, which model a single topological property of connectivity between locations, this method achieves a stronger degree of cognitive adequacy.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122593096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this research is to investigate how to communicate route directions for wayfinding assistance in indoor environments including visible landmarks along the route. We propose an algorithm to automatically generate low level directions, as an XML file, that can be later translated in other languages, e.g., IndoorGML. The most suitable data model is a graph with openings (doors, windows, passages), features and concave corners as nodes, and edges based on geometrical visibility between them. For a given route, the proposed algorithm extracts all the surrounding visible nodes and groups them to simplify subsequent textual instructions. This process is then implemented in a software prototype, "IndoorNav", based on an Android device. It uses QRcode scanning for locating user position, calculates the best route to follow, generates low-level route directions, and translates them into textual instructions in the requested language; finally, it shows them to users.
{"title":"Route directions generation using visible landmarks","authors":"Davide Russo, S. Zlatanova, Eliseo Clementini","doi":"10.1145/2676528.2676530","DOIUrl":"https://doi.org/10.1145/2676528.2676530","url":null,"abstract":"The aim of this research is to investigate how to communicate route directions for wayfinding assistance in indoor environments including visible landmarks along the route. We propose an algorithm to automatically generate low level directions, as an XML file, that can be later translated in other languages, e.g., IndoorGML. The most suitable data model is a graph with openings (doors, windows, passages), features and concave corners as nodes, and edges based on geometrical visibility between them. For a given route, the proposed algorithm extracts all the surrounding visible nodes and groups them to simplify subsequent textual instructions. This process is then implemented in a software prototype, \"IndoorNav\", based on an Android device. It uses QRcode scanning for locating user position, calculates the best route to follow, generates low-level route directions, and translates them into textual instructions in the requested language; finally, it shows them to users.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124887012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There are a number of great attempts to develop an indoor navigation that provide the most optimal path and guidance. Finding a way in large buildings can be a challenging task. In order to represent the real situation to a maximum extent, a representation of the whole room as one single indivisible object is not enough as such representation is very abstract and this could make the navigation difficult and may result into inefficient route planning. In order to provide a smooth navigation path, the presence of humans within the indoor environment and the natural movement of individuals should be taken into consideration. In this paper a two-step indoor space subdivision for indoor navigation is described. Firstly, the indoor space is subdivided into navigable and non-navigable areas considering human perceptions of the environment and human behaviour. Secondly, the navigable space is subdivided applying a constrained Delaunay triangulation. Finally, the guidelines for generation of the navigation network and verification of the proposed model are presented.
{"title":"Indoor space subdivision for indoor navigation","authors":"M. Kruminaite, S. Zlatanova","doi":"10.1145/2676528.2676529","DOIUrl":"https://doi.org/10.1145/2676528.2676529","url":null,"abstract":"There are a number of great attempts to develop an indoor navigation that provide the most optimal path and guidance. Finding a way in large buildings can be a challenging task. In order to represent the real situation to a maximum extent, a representation of the whole room as one single indivisible object is not enough as such representation is very abstract and this could make the navigation difficult and may result into inefficient route planning. In order to provide a smooth navigation path, the presence of humans within the indoor environment and the natural movement of individuals should be taken into consideration. In this paper a two-step indoor space subdivision for indoor navigation is described. Firstly, the indoor space is subdivided into navigable and non-navigable areas considering human perceptions of the environment and human behaviour. Secondly, the navigable space is subdivided applying a constrained Delaunay triangulation. Finally, the guidelines for generation of the navigation network and verification of the proposed model are presented.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127585138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Timothy Ellersiek, G. Andrienko, N. Andrienko, D. Hecker, Hendrik Stange, Marc Mueller
During the past years the interest in the exploitation of mobility information has increased significantly. A growing number of companies and research institutions are interested in the analysis of mobility data with demand of a high level of spatial detail. Means of tracking persons in our environment can nowadays be fulfilled by utilizing several technologies, for example the Bluetooth technology, offering means to obtain movement data. This paper gives an overview of four case studies in the field of Bluetooth tracking which were conducted in order to provide helpful insights on movement aspects for decision makers in their specific microcosm. Aim is to analyse spatio-temporal validity of Bluetooth tracking, and in doing so, to describe the potential of Bluetooth in pedestrian mobility mining.
{"title":"Using Bluetooth to track mobility patterns: depicting its potential based on various case studies","authors":"Timothy Ellersiek, G. Andrienko, N. Andrienko, D. Hecker, Hendrik Stange, Marc Mueller","doi":"10.1145/2533810.2533813","DOIUrl":"https://doi.org/10.1145/2533810.2533813","url":null,"abstract":"During the past years the interest in the exploitation of mobility information has increased significantly. A growing number of companies and research institutions are interested in the analysis of mobility data with demand of a high level of spatial detail. Means of tracking persons in our environment can nowadays be fulfilled by utilizing several technologies, for example the Bluetooth technology, offering means to obtain movement data. This paper gives an overview of four case studies in the field of Bluetooth tracking which were conducted in order to provide helpful insights on movement aspects for decision makers in their specific microcosm. Aim is to analyse spatio-temporal validity of Bluetooth tracking, and in doing so, to describe the potential of Bluetooth in pedestrian mobility mining.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128337035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this study was to investigate how the immersion level of virtual environments (HMD vs. desktop) and rotation method (physical vs. imagined) affects wayfinding performance in multi-story virtual buildings and the development of multi-level cognitive maps. Twelve participants learned multi-level virtual buildings using three VE conditions (physical rotation HMD, physical rotation desktop and imagined rotation desktop). They were then tested on four cross-level tasks, including: pointing, route navigation, vertical navigation, and paper-based drilling. Results showed that performance on between-floor trials was reliably worse than for within-floor trials and that this difference was neither improved by the level of immersion of the display nor the rotation behavior used during navigation. Our data suggest that increasing the fidelity of these interface variables does not yield more accurate development of multi-level cognitive maps. Indeed, multi-level indoor wayfinding performance was as effective with the simplest and least expensive desktop display based purely on joystick navigation as the more complex VE platforms. These findings show that spatial cognition research in multi-level virtual buildings need not be limited to immersive VEs with physical body rotation which require considerable equipment cost and increased technical complexity.
{"title":"The effects of immersion and body-based rotation on learning multi-level indoor virtual environments","authors":"Hengshan Li, N. Giudice","doi":"10.1145/2533810.2533811","DOIUrl":"https://doi.org/10.1145/2533810.2533811","url":null,"abstract":"The goal of this study was to investigate how the immersion level of virtual environments (HMD vs. desktop) and rotation method (physical vs. imagined) affects wayfinding performance in multi-story virtual buildings and the development of multi-level cognitive maps. Twelve participants learned multi-level virtual buildings using three VE conditions (physical rotation HMD, physical rotation desktop and imagined rotation desktop). They were then tested on four cross-level tasks, including: pointing, route navigation, vertical navigation, and paper-based drilling. Results showed that performance on between-floor trials was reliably worse than for within-floor trials and that this difference was neither improved by the level of immersion of the display nor the rotation behavior used during navigation. Our data suggest that increasing the fidelity of these interface variables does not yield more accurate development of multi-level cognitive maps. Indeed, multi-level indoor wayfinding performance was as effective with the simplest and least expensive desktop display based purely on joystick navigation as the more complex VE platforms. These findings show that spatial cognition research in multi-level virtual buildings need not be limited to immersive VEs with physical body rotation which require considerable equipment cost and increased technical complexity.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125502236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Location Based Services (LBS), which are supported by ubiquitous location finding and positioning information, have become increasingly popular. These services are integrated with various wireless technologies (i.e. cellular, WiFi, and Bluetooth) on mobile devices that establish necessary location information. While each of these technologies contributes to the integration, development and success of LBSs, WiFi has been the most widely employed as an alternative to the Global Positioning System (GPS). Several commercial WiFi-based positioning systems (WPS) are available to the public to extend positioning coverage to places where GPS is unreliable or unavailable; however, these commercial WPSs often fail to deliver GPS-like positioning. The coarse positioning accuracy of commercial WPSs may be caused by unreliable or unsecured databases, which contain the essential WiFi-array information to produce local positioning. Knowing this, the quality of WiFi-based positioning services can be enhanced by improving the quality of a database with well-surveyed and accurate information. The Saskatchewan Enhanced positioning System (SaskEPS) is designed to reduce common errors in WPS. SaskEPS's positioning accuracy and consistency is supported by a thoroughly validated Access Point (AP) database. It has been tested in several buildings at the University of Saskatchewan and successfully provides GPS-like positioning accuracy. Our tests have also begun to elucidate the role of WiFi density in ensuring GPS-like positioning accuracy in indoor spaces. In this paper, we investigate the quantitative relationship between WiFi density and SaskEPS's overall positioning accuracy.
{"title":"Quantitative comparison of indoor positioning on different densities of WiFi arrays in a single environment","authors":"W. Jung, S. Bell","doi":"10.1145/2533810.2533816","DOIUrl":"https://doi.org/10.1145/2533810.2533816","url":null,"abstract":"Location Based Services (LBS), which are supported by ubiquitous location finding and positioning information, have become increasingly popular. These services are integrated with various wireless technologies (i.e. cellular, WiFi, and Bluetooth) on mobile devices that establish necessary location information. While each of these technologies contributes to the integration, development and success of LBSs, WiFi has been the most widely employed as an alternative to the Global Positioning System (GPS). Several commercial WiFi-based positioning systems (WPS) are available to the public to extend positioning coverage to places where GPS is unreliable or unavailable; however, these commercial WPSs often fail to deliver GPS-like positioning. The coarse positioning accuracy of commercial WPSs may be caused by unreliable or unsecured databases, which contain the essential WiFi-array information to produce local positioning. Knowing this, the quality of WiFi-based positioning services can be enhanced by improving the quality of a database with well-surveyed and accurate information. The Saskatchewan Enhanced positioning System (SaskEPS) is designed to reduce common errors in WPS. SaskEPS's positioning accuracy and consistency is supported by a thoroughly validated Access Point (AP) database. It has been tested in several buildings at the University of Saskatchewan and successfully provides GPS-like positioning accuracy. Our tests have also begun to elucidate the role of WiFi density in ensuring GPS-like positioning accuracy in indoor spaces. In this paper, we investigate the quantitative relationship between WiFi density and SaskEPS's overall positioning accuracy.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117203279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As mobile videos from smartphones are getting more popular, there have been interests on managing such videos, especially in a large repository. For the management of mobile videos, a new approach has been proposed to organize and search videos using geospatial metadata such as camera location and viewing direction. With the approach, video contents in outdoor space were represented by pure geospatial properties so that well known spatial database technologies can handle video contents more effectively with spatial properties of videos. However, it has been limited by the localization techniques so mainly used for outdoor videos where localization techniques such as GPS is available. Different approaches are required to support geo-tagging of videos in indoor space where no GPS is not available. Due to the recent development of practical indoor localization technique, it becomes possible to tag spatial properties to indoor videos. This work in progress paper introduces a method of automatic geotagging and querying for indoor videos from smartphones.
{"title":"Automatic geotagging and querying of indoor videos","authors":"Joon-Seok Kim, S. H. Kim, Ki-Joune Li","doi":"10.1145/2533810.2533817","DOIUrl":"https://doi.org/10.1145/2533810.2533817","url":null,"abstract":"As mobile videos from smartphones are getting more popular, there have been interests on managing such videos, especially in a large repository. For the management of mobile videos, a new approach has been proposed to organize and search videos using geospatial metadata such as camera location and viewing direction. With the approach, video contents in outdoor space were represented by pure geospatial properties so that well known spatial database technologies can handle video contents more effectively with spatial properties of videos. However, it has been limited by the localization techniques so mainly used for outdoor videos where localization techniques such as GPS is available. Different approaches are required to support geo-tagging of videos in indoor space where no GPS is not available. Due to the recent development of practical indoor localization technique, it becomes possible to tag spatial properties to indoor videos. This work in progress paper introduces a method of automatic geotagging and querying for indoor videos from smartphones.","PeriodicalId":164337,"journal":{"name":"International Symposium on Algorithms","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125271901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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