Name
Abstract | ||
|---|---|---|
To improve the efficiency of drawing the graphic symbols of the scene of traffic accident, a SS-based sketch recognition technology is introduced into the identification of traffic sketches. While four basic cartography factors, including straight line, polyline, circle and arc, are put forward to partition the intricate sketch into the combination of multi-strokes, according to the basic characteristic of the graphics. Online sketch recognition can reveal latent primitive shapes and show the regularized shape on screen immediately through feature recognition, shape fitting and regularization. After the primitive stroke are grouped according to the spatial relationships, the user's intention is caught and suggested through computing their similarity with the predefined templates both in partial structures as well as in overall configuration. Practical application proves the proposed method both effective and efficient. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/FSKD.2010.5569810 | FSKD |
Keywords | Field | DocType |
cartography,graphic recognition,traffic engineering computing,computer graphics,stroke separation,traffic accident,sketch recognition,cartography factor,accidents,feature recognition,shape fitting,ss based sketch recognition,sun,spatial relationships,shape,fitting | Graphics,Line (geometry),Computer vision,Pattern recognition,Sketch-based modeling,Computer science,Feature recognition,Sketch recognition,Regularization (mathematics),Artificial intelligence,Computer graphics,Sketch | Conference |
Volume | ISBN | Citations |
6 | 978-1-4244-5931-5 | 1 |
PageRank | References | Authors |
0.43 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiquan Zhou | 1 | 196 | 13.24 |
| Haiyan Yu | 2 | 1 | 1.11 |
| Zhanfeng Zhao | 3 | 3 | 3.91 |
| Xiaolin Qiao | 4 | 61 | 3.56 |