Abstract
We present a GUI-based C++ toolbox that allows for building distributed, multi-modal context recognition systems by plugging together reusable, parameterizable components. The goals of the toolbox are to simplify the steps from prototypes to online implementations on low-power mobile devices, facilitate portability between platforms and foster easy adaptation and extensibility. The main features of the toolbox we focus on here are a set of parameterizable algorithms including different filters, feature computations and classifiers, a runtime environment that supports complex synchronous and asynchronous data flows, encapsulation of hardware-specific aspects including sensors and data types (e.g., int vs. float), and the ability to outsource parts of the computation to remote devices. In addition, components are provided for group-wise, event-based sensor synchronization and data labeling. We describe the architecture of the toolbox and illustrate its functionality on two case studies that are part of the downloadable distribution.
| Original language | English |
|---|---|
| Title of host publication | Architecture of Computing Systems - ARCS 2006 - 19th International Conference, Proceedings |
| Pages | 99-113 |
| Number of pages | 15 |
| Volume | 3894 LNCS |
| DOIs | |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | 19th International Conference on Architecture of Computing Systems, ARCS 2006 - Frankfurt, Main, Germany Duration: 2006 Mar 13 → 2006 Mar 16 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3894 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 19th International Conference on Architecture of Computing Systems, ARCS 2006 |
|---|---|
| Country | Germany |
| City | Frankfurt, Main |
| Period | 06/3/13 → 06/3/16 |
Fingerprint
ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
Cite this
Distributed modular toolbox for multi-modal context recognition. / Bannach, David; Kunze, Kai Steven; Lukowicz, Paul; Amft, Oliver.
Architecture of Computing Systems - ARCS 2006 - 19th International Conference, Proceedings. Vol. 3894 LNCS 2006. p. 99-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3894 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Distributed modular toolbox for multi-modal context recognition
AU - Bannach, David
AU - Kunze, Kai Steven
AU - Lukowicz, Paul
AU - Amft, Oliver
PY - 2006
Y1 - 2006
N2 - We present a GUI-based C++ toolbox that allows for building distributed, multi-modal context recognition systems by plugging together reusable, parameterizable components. The goals of the toolbox are to simplify the steps from prototypes to online implementations on low-power mobile devices, facilitate portability between platforms and foster easy adaptation and extensibility. The main features of the toolbox we focus on here are a set of parameterizable algorithms including different filters, feature computations and classifiers, a runtime environment that supports complex synchronous and asynchronous data flows, encapsulation of hardware-specific aspects including sensors and data types (e.g., int vs. float), and the ability to outsource parts of the computation to remote devices. In addition, components are provided for group-wise, event-based sensor synchronization and data labeling. We describe the architecture of the toolbox and illustrate its functionality on two case studies that are part of the downloadable distribution.
AB - We present a GUI-based C++ toolbox that allows for building distributed, multi-modal context recognition systems by plugging together reusable, parameterizable components. The goals of the toolbox are to simplify the steps from prototypes to online implementations on low-power mobile devices, facilitate portability between platforms and foster easy adaptation and extensibility. The main features of the toolbox we focus on here are a set of parameterizable algorithms including different filters, feature computations and classifiers, a runtime environment that supports complex synchronous and asynchronous data flows, encapsulation of hardware-specific aspects including sensors and data types (e.g., int vs. float), and the ability to outsource parts of the computation to remote devices. In addition, components are provided for group-wise, event-based sensor synchronization and data labeling. We describe the architecture of the toolbox and illustrate its functionality on two case studies that are part of the downloadable distribution.
UR - http://www.scopus.com/inward/record.url?scp=33745610702&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745610702&partnerID=8YFLogxK
U2 - 10.1007/11682127_8
DO - 10.1007/11682127_8
M3 - Conference contribution
SN - 3540327657
SN - 9783540327653
VL - 3894 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 99
EP - 113
BT - Architecture of Computing Systems - ARCS 2006 - 19th International Conference, Proceedings
ER -