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 |
|---|---|
| Pages | 238-243 |
| Number of pages | 6 |
| Publication status | Published - 2004 Sep 27 |
| Event | 2004 IEEE Intelligent Vehicles Symposium - Parma, Italy Duration: 2004 Jun 14 → 2004 Jun 17 |
Conference
| Conference | 2004 IEEE Intelligent Vehicles Symposium |
|---|---|
| Country | Italy |
| City | Parma |
| Period | 04/6/14 → 04/6/17 |
ASJC Scopus subject areas
- Modelling and Simulation
- Automotive Engineering
- Computer Science Applications
Fingerprint Dive into the research topics of 'Vehicles detection using sensor fusion'. Together they form a unique fingerprint.
Cite this
Takizawa, H., Yamada, K., & Ito, T. (2004). Vehicles detection using sensor fusion. 238-243. Paper presented at 2004 IEEE Intelligent Vehicles Symposium, Parma, Italy.