Abstract
This paper presents a visual-based dimension estimation method for vehicle type classification. Our method extracts moving vehicles from traffic image sequences and fits them with a simple deformable vehicle model. Using a set of coordination mapping functions derived from a calibrated camera model and relying on a shadow removal method, vehicle's width, length and height are estimated. Our experimental tests show that the modeling method is effective and the estimation accuracy is sufficient for general vehicle type classification.
| Original language | English (US) |
|---|---|
| Pages | 201-206 |
| Number of pages | 6 |
| State | Published - Jan 1 2001 |
| Event | 2001 IEEE Intelligent Transportation Systems Proceedings - Oakland, CA, United States Duration: Aug 25 2001 → Aug 29 2001 |
Other
| Other | 2001 IEEE Intelligent Transportation Systems Proceedings |
|---|---|
| Country/Territory | United States |
| City | Oakland, CA |
| Period | 8/25/01 → 8/29/01 |
Keywords
- Camera calibration
- Dimension estimation
- Shadow removal
- Vehicle modeling
ASJC Scopus subject areas
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications