Name
Abstract | ||
|---|---|---|
Model-based activity recognition has been recently proposed as an alternative to signal-oriented recognition. Such model-based approaches seem attractive due to their ability to enable user-independent activity recognition and due to their improved robustness to signal-variation. The first goal of this paper is therefore to systematically analyze the benefit of body-model derived primitives in different sensor settings for multi activity recognition. Furthermore we propose a new body-model based approach using accelerometer sensors only thereby reducing the sensor requirements significantly. Results on a 20 activity dataset indicate that body-model based approaches consistently improve results over signal-oriented approaches. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISWC.2009.32 | Linz |
Keywords | Field | DocType |
sensors,ubiquitous computing,user interfaces,wearable computers,accelerometer sensors,context awareness,model-based activity recognition,sensor-oriented recognition,user-independent activity recognition,wearable computing | Computer vision,Activity recognition,Accelerometer,Computer science,Robustness (computer science),Feature extraction,Context awareness,Artificial intelligence,Ubiquitous computing,User interface,Hidden Markov model,Embedded system | Conference |
ISSN | ISBN | Citations |
1550-4816 | 978-0-7695-3779-5 | 26 |
PageRank | References | Authors |
1.31 | 25 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreas Zinnen | 1 | 26 | 1.31 |
| Ulf Blanke | 2 | 699 | 36.03 |
| Bernt Schiele | 3 | 12901 | 971.29 |