Name
Abstract | ||
|---|---|---|
In mobile and ubiquitous computing environments, acquisition of contextual information about a user Situation is necessary to provide useful services. Although the definition of user context may change according to the situation or the service used, contextual information about who, where, and when are considered to be essential. We have built a test bed with multiple sensors: floor pressure sensors, RFID (radio frequency identification) tag systems, and cameras, to carry out experiments to detect the positions of users and track their movement. The conventional background subtraction method by using cameras was used for moving object detection and tracking. In this paper, we propose knowledge application and parameter adaptation in the background Subtraction method. The results are presented to show that the proposed method decreases the detection errors. |
Year | Venue | Keywords |
|---|---|---|
2008 | COMPUTING AND INFORMATICS | Human tracking, background substruction, parameter adaptation, test bed |
Field | DocType | Volume |
Background subtraction,Object detection,Computer vision,Contextual information,Textual information,Computer science,Testbed,Artificial intelligence,Ubiquitous computing,Multiple sensors,Radio-frequency identification | Journal | 27 |
Issue | ISSN | Citations |
5 | 1335-9150 | 0 |
PageRank | References | Authors |
0.34 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tatsuya Yamazaki | 1 | 143 | 23.02 |
| Tetsuo Toyomura | 2 | 37 | 6.39 |
| Kentaro Kayama | 3 | 22 | 5.57 |
| Seiji Igi | 4 | 83 | 14.01 |