Name
Title | ||
|---|---|---|
A Road Extraction Method by an Active Contour Model with Inertia and Differential Features |
Abstract | ||
|---|---|---|
In this paper we propose a road object extraction technique based on an active contour model (snake) considering inertia and differential features in a movie. Different energy functions can be applicable to snake in order to use information of various objects and various environments. Using many methods for tracking a moving object, snake can be applied to a scene frame by frame. Initial positions of the control points in a frame can refer to the results in the previous frame. We focus on the inertia that works between object shapes in the previous and present frames. In this research inertia is the tendency of a control point to resist its changes in its state of motion in an image space. We introduce an external energy for snake based on inertia of control points. Internal energy functions based on differential features of road geometry are also introduced to extract straight, circular and S-shaped road segments smoothly. The proposed method is applied to extract road geometry from a movie taken by a camera equipped on the flont of a vehicle. Experimental results indicate the availability of the proposed method which is to extract road geometry smoothly and to improve its robustness. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1093/ietisy/e89-d.7.2257 | IEICE Transactions |
Keywords | Field | DocType |
road extraction method,present frame,road object extraction technique,differential feature,research inertia,scene frame,control point,road geometry,differential features,active contour model,previous frame,s-shaped road segment,inertia | Active contour model,Computer vision,Control point,Force field (chemistry),Computer science,Internal energy,Robustness (computer science),Feature extraction,Artificial intelligence,Inertia,Cognitive neuroscience of visual object recognition | Journal |
Volume | Issue | ISSN |
E89-D | 7 | 1745-1361 |
Citations | PageRank | References |
10 | 0.76 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroaki Sawano | 1 | 22 | 7.83 |
| Minoru Okada | 2 | 26 | 7.96 |