Name
Abstract | ||
|---|---|---|
This paper presents an active method for locating objects in images, which is conceptualized mainly by elastically deformable contour model. When an initial model is applied to an image data, it attracts near dominant image features such as edges or lines, but tries to keep its home shape or smooth the deformation if a deformation from the home shape occurs. This model is characterized by the core and the rigidity coefficients which control the shape and strength with the prior knowledge about the expected shape of the object. This mechanism significantly improves the performance of detecting object boundaries in presence of some disturbing image features. The proposed method is validated through a series of experiments, which include tracking objects under nonrigid motion and comparison with the original snake models |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/IROS.1999.812982 | Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference |
Keywords | Field | DocType |
image recognition,object detection,disturbing image features,dominant image features,elastically deformable contour model,image object location,nonrigid motion,object boundary detection,object tracking,rigidity coefficients,snake models | Active contour model,Rigidity (psychology),Active shape model,Object detection,Computer vision,Object-class detection,Feature detection (computer vision),Pattern recognition,Computer science,Feature (computer vision),Haar-like features,Artificial intelligence | Conference |
Volume | ISBN | Citations |
1 | 0-7803-5184-3 | 0 |
PageRank | References | Authors |
0.34 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jae Seon Kim | 1 | 0 | 0.34 |
| Kyoung Chul Koh | 2 | 2 | 2.94 |
| Hyungsuck Cho | 3 | 213 | 24.88 |