Name
Abstract | ||
|---|---|---|
The movement of the vehicle provides useful information for different applications, such as driver assistant systems or autonomous vehicles. This information can be known by means of a GPS, but there are some areas in urban environments where the signal is not available, as tunnels or streets with high buildings. A new method for 2D visual ego motion estimation in urban environments is presented in this paper. This method is based on a stereo-vision system where the feature road points are tracked frame to frame in order to estimate the movement of the vehicle, avoiding outliers from dynamic obstacles. The road profile is used to obtain the world coordinates of the feature points as a unique function of its left image coordinates. For these reasons it is only necessary to search feature points in the lower third of the left images. Moreover, the Kalman filter is used as a solution for filtering problem. That is, in some cases, it is necessary to filter raw data due to noise acquisition of time series. The results of the visual ego motion are compared with raw data from a GPS. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IVS.2012.6232183 | Intelligent Vehicles Symposium |
Keywords | Field | DocType |
Kalman filters,feature extraction,filtering theory,motion estimation,object tracking,road vehicles,stereo image processing,time series,traffic engineering computing,2D visual ego motion estimation,GPS,Kalman filter,U-V disparity,feature points,feature road points,filtering problem,frame-frame tracking,noise acquisition,road profile,stereo-vision system,time series,urban environments,vehicle movement estimation | Computer vision,Computer science,Filtering problem,Kalman filter,Feature extraction,Video tracking,Artificial intelligence,Global Positioning System,Motion estimation,Assisted GPS,Trajectory | Conference |
ISSN | ISBN | Citations |
1931-0587 | 978-1-4673-2119-8 | 3 |
PageRank | References | Authors |
0.43 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Basam Musleh | 1 | 57 | 5.77 |
| David Martín | 2 | 85 | 13.85 |
| Arturo de la Escalera | 3 | 411 | 43.28 |
| José María Armingol | 4 | 213 | 24.74 |
| de la Escalera, A. | 5 | 35 | 2.40 |