Abstract
The sensor fusion method is more robust than the method by using a single sensor. So sensor fusion is effective to vehicle recognition at complex scene. But, if each sensing data processed individually for most stage, recognition performance is not always good. In this paper, we propose the extensible and generalized fusion method. First, fusion vector which is combined between image sensor data and laser radar data at primitive level is prepared. We regard fusion vector as sensing data by one robust sensor. Next, fusion vector is compared with discriminated dictionary. We report efficiency of our method at complex scene which recognition error tend to occur by using a single sensor.
| Original language | English |
|---|---|
| Title of host publication | IEEE Intelligent Vehicles Symposium, Proceedings |
| Pages | 238-243 |
| Number of pages | 6 |
| Publication status | Published - 2004 |
| Externally published | Yes |
| Event | 2004 IEEE Intelligent Vehicles Symposium - Parma Duration: 2004 Jun 14 → 2004 Jun 17 |
Other
| Other | 2004 IEEE Intelligent Vehicles Symposium |
|---|---|
| City | Parma |
| Period | 04/6/14 → 04/6/17 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Vehicles detection using sensor fusion. / Takizawa, Hiroomi; Yamada, Kenichi; Ito, Toshio.
IEEE Intelligent Vehicles Symposium, Proceedings. 2004. p. 238-243.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Vehicles detection using sensor fusion
AU - Takizawa, Hiroomi
AU - Yamada, Kenichi
AU - Ito, Toshio
PY - 2004
Y1 - 2004
N2 - The sensor fusion method is more robust than the method by using a single sensor. So sensor fusion is effective to vehicle recognition at complex scene. But, if each sensing data processed individually for most stage, recognition performance is not always good. In this paper, we propose the extensible and generalized fusion method. First, fusion vector which is combined between image sensor data and laser radar data at primitive level is prepared. We regard fusion vector as sensing data by one robust sensor. Next, fusion vector is compared with discriminated dictionary. We report efficiency of our method at complex scene which recognition error tend to occur by using a single sensor.
AB - The sensor fusion method is more robust than the method by using a single sensor. So sensor fusion is effective to vehicle recognition at complex scene. But, if each sensing data processed individually for most stage, recognition performance is not always good. In this paper, we propose the extensible and generalized fusion method. First, fusion vector which is combined between image sensor data and laser radar data at primitive level is prepared. We regard fusion vector as sensing data by one robust sensor. Next, fusion vector is compared with discriminated dictionary. We report efficiency of our method at complex scene which recognition error tend to occur by using a single sensor.
UR - http://www.scopus.com/inward/record.url?scp=4544313431&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4544313431&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:4544313431
SP - 238
EP - 243
BT - IEEE Intelligent Vehicles Symposium, Proceedings
ER -