Abstract
How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).
| Original language | English |
|---|---|
| Title of host publication | Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013 |
| Pages | 3 |
| Number of pages | 1 |
| DOIs | |
| Publication status | Published - 2013 |
| Externally published | Yes |
| Event | Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013 - Beijing, China Duration: 2013 Aug 4 → 2013 Aug 5 |
Other
| Other | Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 13/8/4 → 13/8/5 |
Fingerprint
Keywords
- activity recognition
- reading behavior
- robust
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
Real-life activity recognition : Recognizing reading activities. / Kunze, Kai Steven.
Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013. 2013. p. 3.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Real-life activity recognition
T2 - Recognizing reading activities
AU - Kunze, Kai Steven
PY - 2013
Y1 - 2013
N2 - How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).
AB - How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).
KW - activity recognition
KW - reading behavior
KW - robust
UR - http://www.scopus.com/inward/record.url?scp=84891107778&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891107778&partnerID=8YFLogxK
U2 - 10.1145/2516911.2516912
DO - 10.1145/2516911.2516912
M3 - Conference contribution
AN - SCOPUS:84891107778
SN - 9781450323468
SP - 3
BT - Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013
ER -