The Experts below are selected from a list of 49413 Experts worldwide ranked by ideXlab platform
Gudrun Klinker - One of the best experts on this subject based on the ideXlab platform.
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Automatic configuration of pervasive sensor networks for augmented reality
IEEE Pervasive Computing, 2011Co-Authors: Daniel Pustka, Manuel Huber, Christian Waechter, Peter Keitler, Joseph Newman, Dieter Schmalstieg, Florian Echtler, Gudrun KlinkerAbstract:The ubiquitous tracking (Ubitrack) approach uses Spatial Relationship graphs and patterns to support a distributed software architecture for augmented reality (AR) systems in which clients can produce, transform, transmit, and consume tracking data.
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Integrating Gyroscopes into Ubiquitous Tracking Environments
2008 IEEE Virtual Reality Conference, 2008Co-Authors: Daniel Pustka, Manuel Huber, Gudrun KlinkerAbstract:It is widely recognized that inertial sensors, in particular gyroscopes, can improve the latency and accuracy of orientation tracking by fusing the inertial measurements with data from other sensors. In our previous work, we introduced the concepts of Spatial Relationship graphs and Spatial Relationship patterns to formally model multi-sensor tracking setups and derive valid applications of well-known algorithms in order to infer new Spatial Relationships for tracking and calibration. In this work, we extend our approach by providing additional Spatial Relationship patterns that transform incremental rotations and add gyroscope alignment and fusion. The usefulness of the resulting tracking configurations is evaluated in two different scenarios with both inside-out and outside-in tracking.
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A System Architecture for Ubiquitous Tracking Environments
2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007Co-Authors: Manuel Huber, Daniel Pustka, Peter Keitler, Florian Echtler, Gudrun KlinkerAbstract:Ubiquitous tracking setups, covering large tracking areas with many heterogeneous sensors of varying accuracy, require dedicated middleware to facilitate development of stationary and mobile applications by providing a simple interface and encapsulating the details of sensing, calibration and sensor fusion. In this paper we present a centrally coordinated peer-to-peer architecture for ubiquitous tracking, where a server computes optimal data flow configurations for sensor and application clients, which are directly exchanging tracking data with low latency using a light-weight data flow framework. The server's decisions are inferred from an actively maintained central Spatial Relationship graph (SRG) using Spatial Relationship patterns. The system is compared to a previous Ubitrack implementation using the highly distributed DWARF middleware. It exhibits significantly better performance in a reference scenario.
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Spatial Relationship patterns: elements of reusable tracking and calibration systems
2006 IEEE ACM International Symposium on Mixed and Augmented Reality, 2006Co-Authors: Daniel Pustka, Manuel Huber, Martin Bauer, Gudrun KlinkerAbstract:With tracking setups becoming increasingly complex, it gets more difficult to find suitable algorithms for tracking, calibration and sensor fusion. A large number of solutions exists in the literature for various combinations of sensors, however, no development methodology is available for systematic analysis of tracking setups. When modeling a system as a Spatial Relationship graph (SRG), which describes coordinate systems and known transformations, all algorithms used for tracking and calibration correspond to certain patterns in the graph. This paper introduces a formal model for representing such Spatial Relationship patterns and presents a small catalog of patterns frequently used in augmented reality systems. We also describe an algorithm to identify patterns in SRGs at runtime for automatic construction of data flows networks for tracking and calibration.
Maria Elena Gallina - One of the best experts on this subject based on the ideXlab platform.
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resolving the Spatial Relationship between intracellular components by dual color super resolution optical fluctuations imaging sofi
Optical nanoscopy, 2013Co-Authors: Maria Elena Gallina, Jianmin Xu, Thomas Dertinger, Adva Aizer, Yaron Shavtal, Shimon WeissAbstract:Multi-color super-resolution (SR) imaging microscopy techniques can resolve ultrastructural Relationships between- and provide co-localization information of- different proteins inside the cell or even within organelles at a higher resolution than afforded by conventional diffraction-limited imaging. While still very challenging, important SR colocalization results have been reported in recent years using STED, PALM and STORM techniques. In this work, we demonstrate dual-color Super Resolution Optical Fluctuations Imaging (SOFI) using a standard far-field fluorescence microscope and different color blinking quantum dots. We define the Spatial Relationship between hDcp1a, a processing body (P-body, PB) protein, and the tubulin cytoskeletal network. Our finding could open up new perspectives on the role of the cytoskeleton in PB formation and assembly. Further insights into PB internal organization are also reported and discussed. Our results demonstrate the suitability and facile use of multi-color SOFI for the investigation of intracellular ultrastructures.
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Resolving the Spatial Relationship between intracellular components by dual color super resolution optical fluctuations imaging (SOFI)
Optical Nanoscopy, 2013Co-Authors: Maria Elena Gallina, Jianmin Xu, Thomas Dertinger, Adva Aizer, Yaron Shav-tal, Shimon WeissAbstract:Background Multi-color super-resolution (SR) imaging microscopy techniques can resolve ultrastructural Relationships between- and provide co-localization information of- different proteins inside the cell or even within organelles at a higher resolution than afforded by conventional diffraction-limited imaging. While still very challenging, important SR colocalization results have been reported in recent years using STED, PALM and STORM techniques. Results In this work, we demonstrate dual-color Super Resolution Optical Fluctuations Imaging (SOFI) using a standard far-field fluorescence microscope and different color blinking quantum dots. We define the Spatial Relationship between hDcp1a, a processing body (P-body, PB) protein, and the tubulin cytoskeletal network. Our finding could open up new perspectives on the role of the cytoskeleton in PB formation and assembly. Further insights into PB internal organization are also reported and discussed. Conclusions Our results demonstrate the suitability and facile use of multi-color SOFI for the investigation of intracellular ultrastructures.
Shimon Weiss - One of the best experts on this subject based on the ideXlab platform.
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resolving the Spatial Relationship between intracellular components by dual color super resolution optical fluctuations imaging sofi
Optical nanoscopy, 2013Co-Authors: Maria Elena Gallina, Jianmin Xu, Thomas Dertinger, Adva Aizer, Yaron Shavtal, Shimon WeissAbstract:Multi-color super-resolution (SR) imaging microscopy techniques can resolve ultrastructural Relationships between- and provide co-localization information of- different proteins inside the cell or even within organelles at a higher resolution than afforded by conventional diffraction-limited imaging. While still very challenging, important SR colocalization results have been reported in recent years using STED, PALM and STORM techniques. In this work, we demonstrate dual-color Super Resolution Optical Fluctuations Imaging (SOFI) using a standard far-field fluorescence microscope and different color blinking quantum dots. We define the Spatial Relationship between hDcp1a, a processing body (P-body, PB) protein, and the tubulin cytoskeletal network. Our finding could open up new perspectives on the role of the cytoskeleton in PB formation and assembly. Further insights into PB internal organization are also reported and discussed. Our results demonstrate the suitability and facile use of multi-color SOFI for the investigation of intracellular ultrastructures.
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Resolving the Spatial Relationship between intracellular components by dual color super resolution optical fluctuations imaging (SOFI)
Optical Nanoscopy, 2013Co-Authors: Maria Elena Gallina, Jianmin Xu, Thomas Dertinger, Adva Aizer, Yaron Shav-tal, Shimon WeissAbstract:Background Multi-color super-resolution (SR) imaging microscopy techniques can resolve ultrastructural Relationships between- and provide co-localization information of- different proteins inside the cell or even within organelles at a higher resolution than afforded by conventional diffraction-limited imaging. While still very challenging, important SR colocalization results have been reported in recent years using STED, PALM and STORM techniques. Results In this work, we demonstrate dual-color Super Resolution Optical Fluctuations Imaging (SOFI) using a standard far-field fluorescence microscope and different color blinking quantum dots. We define the Spatial Relationship between hDcp1a, a processing body (P-body, PB) protein, and the tubulin cytoskeletal network. Our finding could open up new perspectives on the role of the cytoskeleton in PB formation and assembly. Further insights into PB internal organization are also reported and discussed. Conclusions Our results demonstrate the suitability and facile use of multi-color SOFI for the investigation of intracellular ultrastructures.
Daniel Pustka - One of the best experts on this subject based on the ideXlab platform.
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Automatic configuration of pervasive sensor networks for augmented reality
IEEE Pervasive Computing, 2011Co-Authors: Daniel Pustka, Manuel Huber, Christian Waechter, Peter Keitler, Joseph Newman, Dieter Schmalstieg, Florian Echtler, Gudrun KlinkerAbstract:The ubiquitous tracking (Ubitrack) approach uses Spatial Relationship graphs and patterns to support a distributed software architecture for augmented reality (AR) systems in which clients can produce, transform, transmit, and consume tracking data.
-
Integrating Gyroscopes into Ubiquitous Tracking Environments
2008 IEEE Virtual Reality Conference, 2008Co-Authors: Daniel Pustka, Manuel Huber, Gudrun KlinkerAbstract:It is widely recognized that inertial sensors, in particular gyroscopes, can improve the latency and accuracy of orientation tracking by fusing the inertial measurements with data from other sensors. In our previous work, we introduced the concepts of Spatial Relationship graphs and Spatial Relationship patterns to formally model multi-sensor tracking setups and derive valid applications of well-known algorithms in order to infer new Spatial Relationships for tracking and calibration. In this work, we extend our approach by providing additional Spatial Relationship patterns that transform incremental rotations and add gyroscope alignment and fusion. The usefulness of the resulting tracking configurations is evaluated in two different scenarios with both inside-out and outside-in tracking.
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A System Architecture for Ubiquitous Tracking Environments
2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007Co-Authors: Manuel Huber, Daniel Pustka, Peter Keitler, Florian Echtler, Gudrun KlinkerAbstract:Ubiquitous tracking setups, covering large tracking areas with many heterogeneous sensors of varying accuracy, require dedicated middleware to facilitate development of stationary and mobile applications by providing a simple interface and encapsulating the details of sensing, calibration and sensor fusion. In this paper we present a centrally coordinated peer-to-peer architecture for ubiquitous tracking, where a server computes optimal data flow configurations for sensor and application clients, which are directly exchanging tracking data with low latency using a light-weight data flow framework. The server's decisions are inferred from an actively maintained central Spatial Relationship graph (SRG) using Spatial Relationship patterns. The system is compared to a previous Ubitrack implementation using the highly distributed DWARF middleware. It exhibits significantly better performance in a reference scenario.
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Spatial Relationship patterns: elements of reusable tracking and calibration systems
2006 IEEE ACM International Symposium on Mixed and Augmented Reality, 2006Co-Authors: Daniel Pustka, Manuel Huber, Martin Bauer, Gudrun KlinkerAbstract:With tracking setups becoming increasingly complex, it gets more difficult to find suitable algorithms for tracking, calibration and sensor fusion. A large number of solutions exists in the literature for various combinations of sensors, however, no development methodology is available for systematic analysis of tracking setups. When modeling a system as a Spatial Relationship graph (SRG), which describes coordinate systems and known transformations, all algorithms used for tracking and calibration correspond to certain patterns in the graph. This paper introduces a formal model for representing such Spatial Relationship patterns and presents a small catalog of patterns frequently used in augmented reality systems. We also describe an algorithm to identify patterns in SRGs at runtime for automatic construction of data flows networks for tracking and calibration.
Manuel Huber - One of the best experts on this subject based on the ideXlab platform.
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Automatic configuration of pervasive sensor networks for augmented reality
IEEE Pervasive Computing, 2011Co-Authors: Daniel Pustka, Manuel Huber, Christian Waechter, Peter Keitler, Joseph Newman, Dieter Schmalstieg, Florian Echtler, Gudrun KlinkerAbstract:The ubiquitous tracking (Ubitrack) approach uses Spatial Relationship graphs and patterns to support a distributed software architecture for augmented reality (AR) systems in which clients can produce, transform, transmit, and consume tracking data.
-
Integrating Gyroscopes into Ubiquitous Tracking Environments
2008 IEEE Virtual Reality Conference, 2008Co-Authors: Daniel Pustka, Manuel Huber, Gudrun KlinkerAbstract:It is widely recognized that inertial sensors, in particular gyroscopes, can improve the latency and accuracy of orientation tracking by fusing the inertial measurements with data from other sensors. In our previous work, we introduced the concepts of Spatial Relationship graphs and Spatial Relationship patterns to formally model multi-sensor tracking setups and derive valid applications of well-known algorithms in order to infer new Spatial Relationships for tracking and calibration. In this work, we extend our approach by providing additional Spatial Relationship patterns that transform incremental rotations and add gyroscope alignment and fusion. The usefulness of the resulting tracking configurations is evaluated in two different scenarios with both inside-out and outside-in tracking.
-
A System Architecture for Ubiquitous Tracking Environments
2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007Co-Authors: Manuel Huber, Daniel Pustka, Peter Keitler, Florian Echtler, Gudrun KlinkerAbstract:Ubiquitous tracking setups, covering large tracking areas with many heterogeneous sensors of varying accuracy, require dedicated middleware to facilitate development of stationary and mobile applications by providing a simple interface and encapsulating the details of sensing, calibration and sensor fusion. In this paper we present a centrally coordinated peer-to-peer architecture for ubiquitous tracking, where a server computes optimal data flow configurations for sensor and application clients, which are directly exchanging tracking data with low latency using a light-weight data flow framework. The server's decisions are inferred from an actively maintained central Spatial Relationship graph (SRG) using Spatial Relationship patterns. The system is compared to a previous Ubitrack implementation using the highly distributed DWARF middleware. It exhibits significantly better performance in a reference scenario.
-
Spatial Relationship patterns: elements of reusable tracking and calibration systems
2006 IEEE ACM International Symposium on Mixed and Augmented Reality, 2006Co-Authors: Daniel Pustka, Manuel Huber, Martin Bauer, Gudrun KlinkerAbstract:With tracking setups becoming increasingly complex, it gets more difficult to find suitable algorithms for tracking, calibration and sensor fusion. A large number of solutions exists in the literature for various combinations of sensors, however, no development methodology is available for systematic analysis of tracking setups. When modeling a system as a Spatial Relationship graph (SRG), which describes coordinate systems and known transformations, all algorithms used for tracking and calibration correspond to certain patterns in the graph. This paper introduces a formal model for representing such Spatial Relationship patterns and presents a small catalog of patterns frequently used in augmented reality systems. We also describe an algorithm to identify patterns in SRGs at runtime for automatic construction of data flows networks for tracking and calibration.
