Name
Abstract | ||
|---|---|---|
A method to detect moving objects on non-stationary background is proposed. The concurrent motions of foreground and background pixels make it extremely difficult to maintain a plausible background model for background subtraction. In our method, motion fields of aligned neighboring frames are fused to reduce parallax effects in moving blob detection. A fused color background model is further developed to refine shapes of detected objects. Finally, moving blob information is incorporated into the adaptation process of background model. Only confidently marked background pixels are adapted into background models with each incoming frame. Experimental results shown robust, well-shaped moving object detection can be obtained under unconstrained scenes. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICCCN.2007.4317979 | PROCEEDINGS - 16TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS, VOLS 1-3 |
Keywords | Field | DocType |
object detection, optical flow, background modeling | Background subtraction,Object detection,Computer vision,Computer graphics (images),Parallax,Computer science,Blob detection,Pixel,Artificial intelligence,Optical flow | Conference |
ISSN | Citations | PageRank |
1095-2055 | 3 | 0.41 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ming-Yu Shih | 1 | 72 | 8.65 |
| Yao-jen Chang | 2 | 396 | 47.11 |
| Bwo-chau Fu | 3 | 5 | 0.83 |
| Ching-chun Huang | 4 | 135 | 9.63 |