Name
Abstract | ||
|---|---|---|
In this paper, we detail a complete software architecture of a key task that an intelligent vehicle has to deal with: frontal object perception. This task is solved by processing raw data of a radar and a mono-camera to detect and track moving objects. Data sets obtained from highways, country roads and urban areas were used to test the proposed method. Several experiments were conducted to show that the proposed method obtains a better environment representation, i.e., reduces the false alarms and missed detections from individual sensor evidence. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IVS.2012.6232307 | Intelligent Vehicles Symposium |
Keywords | Field | DocType |
driver information systems,object detection,object tracking,road vehicle radar,complete software architecture,country roads,frontal object perception,highways,intelligent vehicle,monovision,moving objects detection,moving objects tracking,radar,urban areas | Radar,Computer vision,Object detection,Data set,Radar tracker,Computer science,Raw data,Video tracking,Artificial intelligence,Software architecture,Detector | Conference |
ISSN | ISBN | Citations |
1931-0587 | 978-1-4673-2119-8 | 9 |
PageRank | References | Authors |
0.63 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Omar Chávez García | 1 | 11 | 1.24 |
| Julien Burlet | 2 | 58 | 6.14 |
| Trung-Dung Vu | 3 | 76 | 6.57 |
| Olivier Aycard | 4 | 309 | 26.57 |