Name
Abstract | ||
|---|---|---|
In this paper, we propose a low complexity method for detection and tracking of potholes in video sequences taken by a camera placed inside a moving car. The region of interest for the detection of the potholes is selected as the image area where the road is observed with the highest resolution. A threshold-based algorithm generates a set of candidate regions. For each region the following features are extracted: its size, the regularity of the intensity surface, contrast with respect to background model, and the region's contour length and shape. The candidate regions are labeled as putative potholes by a decision tree according to these features, eliminating the false positives due to shadows of wayside objects. The putative potholes that are successfully tracked in consecutive frames are finally declared potholes. Experimental results with real video sequences show a good detection precision. |
Year | Venue | Keywords |
|---|---|---|
2016 | 2016 39TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) | Pothole detection, pothole tracking, reflection in windshield, region of interest, Euclidean distance mapping |
Field | DocType | Citations |
Computer vision,Decision tree,Algorithm design,Computer science,Feature extraction,Artificial intelligence,Region of interest,False positive paradox | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. Schiopu | 1 | 37 | 8.04 |
| Jukka Saarinen | 2 | 264 | 46.21 |
| Lauri Kettunen | 3 | 0 | 2.03 |
| Ioan Tabus | 4 | 276 | 38.23 |