The localization of persons or objects usually refers to a position determined in a spatial reference system.Outdoors,this is usually accomplished with Global Navigation Satellite Systems(GNSS).However,the automatic p...The localization of persons or objects usually refers to a position determined in a spatial reference system.Outdoors,this is usually accomplished with Global Navigation Satellite Systems(GNSS).However,the automatic positioning of people in GNSS-free environments,especially inside of buildings(indoors)poses a huge challenge.Indoors,satellite signals are attenuated,shielded or reflected by building components(e.g.walls or ceilings).For selected applications,the automatic indoor positioning is possible based on different technologies(e.g.WiFi,RFID,or UWB).However,a standard solution is still not available.Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions,e.g.additional infrastructures or sensor technologies.Smartphones,as popular cost-effective multi-sensor systems,is a promising indoor localization platform for the mass-market and is increasingly coming into focus.Today’s devices are equipped with a variety of sensors that can be used for indoor positioning.In this contribution,an approach to smartphone-based pedestrian indoor localization is presented.The novelty of this approach refers to a holistic,real-time pedestrian localization inside of buildings based on multisensor smartphones and easy-to-install local positioning systems.For this purpose,the barometric altitude is estimated in order to derive the floor on which the user is located.The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors.In order to minimize the strong error accumulation in the localization caused by various sensor errors,additional information is integrated into the position estimation.The building model is used to identify permissible(e.g.rooms,passageways)and impermissible(e.g.walls)building areas for the pedestrian.Several technologies contributing to higher precision and robustness are also included.For the fusion of different linear and non-linear data,an advanced algorithm based on the Sequential Monte Carlo method is presented.展开更多
Real-time geospatial information is used in various applications such as risk management or alerting services.Especially,the rise of new sensing technologies also increases the demand for processing the data in real t...Real-time geospatial information is used in various applications such as risk management or alerting services.Especially,the rise of new sensing technologies also increases the demand for processing the data in real time.Today’s spatial data infrastructures,however,do not meet the requirements for real-time geoprocessing.The OpenGIS®Web Processing Service(WPS)is not designed to process real-time workflows.It has some major drawbacks in asynchronous processing and cannot handle(geo)data streams out of the box.In previous papers,we introduced the GeoPipes approach to share spatiotemporal data in real time.We implemented the concept extending the Message Queue and Telemetry Transport(MQTT)protocol by a spatial and temporal dimension,which we call GeoMQTT.In this paper,we demonstrate the integration of the GeoPipes idea in the WPS interface to expose standardized real-time geoprocessing services.The proof of the concept is illustrated in some exemplary real-time geo processes.展开更多
Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the ...Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the registration problem increases dramatically as the number of stems grows.It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans.This paper presents an automatic and fast registration of TLS point clouds in forest areas.It reduces stems by selecting from the overlap areas,which are recovered from the mode-based key points that are detected from crowns.The proposed method was tested in a managed forest in Finland,and was compared with the stem-based registration method without reducing stems.The experiments demonstrated that the mean rotation error was 2.09′,and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm,respectively.Compared with the stem-based method,the proposed method improves the registration efficiency significantly(818 s vs 96 s)and achieves similar results in terms of the mean registration errors(1.94′for rotation error,0.83 and 7.38 cm for horizontal and vertical translation error,respectively).展开更多
CityGML,a semantic information model for digital/virtual city models has become quite popular in various scenarios.While the data format is still actively under development,it is already supported by different softwar...CityGML,a semantic information model for digital/virtual city models has become quite popular in various scenarios.While the data format is still actively under development,it is already supported by different software solutions,especially GIS-based desktop applications.Mobile systems on the other hand are still neglected,even though the georeferenced objects of CityGML have many application fields,for example,in the currently popular area of location-based Augmented Reality.In this paper we present an independent multi-platform CityGML viewer,its architecture and specific implementation techniques that we use to realize and optimize the process of visualizing CityGML data for use in Augmented Reality.The main focus lies in improving the implementation on mobile devices,such as smartphones,and assessing its usability and performance in comparison to web-based approaches.Due to the constrained hardware resources of smartphones,it is a particular challenge to handle complex 3D objects and large virtual worlds as provided by CityGML,not only in terms of memory and storage space,but also with respect to mobile processing units and display sizes.展开更多
Many augmented reality(AR)systems are developed for entertainment,but AR and particularly mobile AR potentially have more application possibilities in other fields.For example,in civil engineering or city planning,AR ...Many augmented reality(AR)systems are developed for entertainment,but AR and particularly mobile AR potentially have more application possibilities in other fields.For example,in civil engineering or city planning,AR could be used in combination with CityGML building models to enhance some typical workflows in planning,execution and operation processes.A concrete example is the geo-referenced on-site visualization of planned buildings or building parts,to simplify planning processes and optimize the communication between the participating decision-makers.One of the main challenges for the visualization lies in the pose tracking,i.e.the real-time estimation of the translation and rotation of the mobile device to align the virtual objects with reality.In this paper,we introduce a proof-of-concept fine-grained mobile AR CityGML-based pose tracking system aimed at the mentioned applications.The system estimates poses by combining 3D CityGML data with information derived from 2D camera images and an inertial measurement unit and is fully self-sufficient and operates without external infrastructure.The results of our evaluation show that CityGML and low-cost off-the-shelf mobile devices,such as smartphones,already provide performant and accurate mobile pose tracking for AR in civil engineering and city planning.展开更多
As a state-of-the-art mapping technology,mobile laser scanning(MLS)is increasingly applied to fields such as digital presentations of city environments.However,its application has recently met a bottleneck in data pro...As a state-of-the-art mapping technology,mobile laser scanning(MLS)is increasingly applied to fields such as digital presentations of city environments.However,its application has recently met a bottleneck in data processing.It has been found that conventional methods for geometrically modeling 3D scattered points are inadequate when dealing with large volumes of MLS data.In fact,this is a challenge that has already been noted in the MLS-relevant fields,e.g.remote sensing,robot perception,and pattern recognition.A variety of algorithms under the schematic frame of analysis,modeling and synthesis(AMS)have been developed in these fields.The AMS paradigm is to first extract the implicit geometric primitives within each scan profile by geometrically modeling its 2D scattered points(GM2P).The resultant 2D geometric primitives are then integrated to restore the real 3D geometrical models.In this process,GM2P is a kernel procedure whereby a review of the GM2P algorithms is assumed to be of significance for developing new efficient algorithms for geometrically modeling 3D scattered points.This idea is supported by MLS sampling often being executed via parallel scan profiles.Indeed,the results of the literature review indicate an avenue for methodologically improving MLS in data processing.展开更多
文摘The localization of persons or objects usually refers to a position determined in a spatial reference system.Outdoors,this is usually accomplished with Global Navigation Satellite Systems(GNSS).However,the automatic positioning of people in GNSS-free environments,especially inside of buildings(indoors)poses a huge challenge.Indoors,satellite signals are attenuated,shielded or reflected by building components(e.g.walls or ceilings).For selected applications,the automatic indoor positioning is possible based on different technologies(e.g.WiFi,RFID,or UWB).However,a standard solution is still not available.Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions,e.g.additional infrastructures or sensor technologies.Smartphones,as popular cost-effective multi-sensor systems,is a promising indoor localization platform for the mass-market and is increasingly coming into focus.Today’s devices are equipped with a variety of sensors that can be used for indoor positioning.In this contribution,an approach to smartphone-based pedestrian indoor localization is presented.The novelty of this approach refers to a holistic,real-time pedestrian localization inside of buildings based on multisensor smartphones and easy-to-install local positioning systems.For this purpose,the barometric altitude is estimated in order to derive the floor on which the user is located.The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors.In order to minimize the strong error accumulation in the localization caused by various sensor errors,additional information is integrated into the position estimation.The building model is used to identify permissible(e.g.rooms,passageways)and impermissible(e.g.walls)building areas for the pedestrian.Several technologies contributing to higher precision and robustness are also included.For the fusion of different linear and non-linear data,an advanced algorithm based on the Sequential Monte Carlo method is presented.
文摘Real-time geospatial information is used in various applications such as risk management or alerting services.Especially,the rise of new sensing technologies also increases the demand for processing the data in real time.Today’s spatial data infrastructures,however,do not meet the requirements for real-time geoprocessing.The OpenGIS®Web Processing Service(WPS)is not designed to process real-time workflows.It has some major drawbacks in asynchronous processing and cannot handle(geo)data streams out of the box.In previous papers,we introduced the GeoPipes approach to share spatiotemporal data in real time.We implemented the concept extending the Message Queue and Telemetry Transport(MQTT)protocol by a spatial and temporal dimension,which we call GeoMQTT.In this paper,we demonstrate the integration of the GeoPipes idea in the WPS interface to expose standardized real-time geoprocessing services.The proof of the concept is illustrated in some exemplary real-time geo processes.
基金funded by the Key Program of the National Natural Science Foundation of China(No.41531177)the National Natural Science Foundation of China(No.41901403)+1 种基金the National Science Fund for Distinguished Young Scholars of China(No.41725005)Academy of Finland,Strategic Research Council at the Academy of Finland is gratefully acknowledged through project(314312)as well as Academy of Finland through projects(334830,334829,300066).
文摘Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the registration problem increases dramatically as the number of stems grows.It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans.This paper presents an automatic and fast registration of TLS point clouds in forest areas.It reduces stems by selecting from the overlap areas,which are recovered from the mode-based key points that are detected from crowns.The proposed method was tested in a managed forest in Finland,and was compared with the stem-based registration method without reducing stems.The experiments demonstrated that the mean rotation error was 2.09′,and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm,respectively.Compared with the stem-based method,the proposed method improves the registration efficiency significantly(818 s vs 96 s)and achieves similar results in terms of the mean registration errors(1.94′for rotation error,0.83 and 7.38 cm for horizontal and vertical translation error,respectively).
文摘CityGML,a semantic information model for digital/virtual city models has become quite popular in various scenarios.While the data format is still actively under development,it is already supported by different software solutions,especially GIS-based desktop applications.Mobile systems on the other hand are still neglected,even though the georeferenced objects of CityGML have many application fields,for example,in the currently popular area of location-based Augmented Reality.In this paper we present an independent multi-platform CityGML viewer,its architecture and specific implementation techniques that we use to realize and optimize the process of visualizing CityGML data for use in Augmented Reality.The main focus lies in improving the implementation on mobile devices,such as smartphones,and assessing its usability and performance in comparison to web-based approaches.Due to the constrained hardware resources of smartphones,it is a particular challenge to handle complex 3D objects and large virtual worlds as provided by CityGML,not only in terms of memory and storage space,but also with respect to mobile processing units and display sizes.
文摘Many augmented reality(AR)systems are developed for entertainment,but AR and particularly mobile AR potentially have more application possibilities in other fields.For example,in civil engineering or city planning,AR could be used in combination with CityGML building models to enhance some typical workflows in planning,execution and operation processes.A concrete example is the geo-referenced on-site visualization of planned buildings or building parts,to simplify planning processes and optimize the communication between the participating decision-makers.One of the main challenges for the visualization lies in the pose tracking,i.e.the real-time estimation of the translation and rotation of the mobile device to align the virtual objects with reality.In this paper,we introduce a proof-of-concept fine-grained mobile AR CityGML-based pose tracking system aimed at the mentioned applications.The system estimates poses by combining 3D CityGML data with information derived from 2D camera images and an inertial measurement unit and is fully self-sufficient and operates without external infrastructure.The results of our evaluation show that CityGML and low-cost off-the-shelf mobile devices,such as smartphones,already provide performant and accurate mobile pose tracking for AR in civil engineering and city planning.
文摘As a state-of-the-art mapping technology,mobile laser scanning(MLS)is increasingly applied to fields such as digital presentations of city environments.However,its application has recently met a bottleneck in data processing.It has been found that conventional methods for geometrically modeling 3D scattered points are inadequate when dealing with large volumes of MLS data.In fact,this is a challenge that has already been noted in the MLS-relevant fields,e.g.remote sensing,robot perception,and pattern recognition.A variety of algorithms under the schematic frame of analysis,modeling and synthesis(AMS)have been developed in these fields.The AMS paradigm is to first extract the implicit geometric primitives within each scan profile by geometrically modeling its 2D scattered points(GM2P).The resultant 2D geometric primitives are then integrated to restore the real 3D geometrical models.In this process,GM2P is a kernel procedure whereby a review of the GM2P algorithms is assumed to be of significance for developing new efficient algorithms for geometrically modeling 3D scattered points.This idea is supported by MLS sampling often being executed via parallel scan profiles.Indeed,the results of the literature review indicate an avenue for methodologically improving MLS in data processing.
