Name
Abstract | ||
|---|---|---|
Detecting foreground object often need to face the problems of illumination change and image noise. In this paper, we propose an object detection method using two successive image frames. Illumination change would be very small in such short time, and then we can handle the first problem more easily. Image noise will confuse the detection of an object boundary. To handle this problem, we apply level set method to enclose the foreground object regions. The experiments show that our method can be applied to extract foreground objects in various environments and different cameras. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/AVSS.2008.25 | AVSS |
Keywords | Field | DocType |
successive image frame,video signal processing,different camera,illumination change,foreground object,foreground object region,foreground object detection,object boundary,image noise,successive images,image sequences,object boundary detection,object detection,detecting foreground,object detection method,level set method,successive image frames,lighting,pixel,level set,data mining | Object detection,Computer vision,Viola–Jones object detection framework,Object-class detection,Pattern recognition,Computer science,Level set method,Level set,Image noise,Artificial intelligence,Pixel | Conference |
ISBN | Citations | PageRank |
978-0-7695-3422-0 | 1 | 0.36 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. M. Wang | 1 | 11 | 2.90 |
| Shen Cherng | 2 | 42 | 4.29 |
| Chiou-Shann Fuh | 3 | 647 | 56.08 |
| Sei-Wang Chen | 4 | 311 | 29.23 |