Name
Title | ||
|---|---|---|
Foreground detection: Combining background subspace learning with object smoothing model |
Abstract | ||
|---|---|---|
Foreground detection is a challenging problem in complex scenes. In this paper, a novel foreground detection method is proposed which combines background subspace learning with object smoothing model. Considering background scenes in consecutive frames are almost the same, they are approximated using an efficient subspace learning technique which is based on 2D images. Due to the pixels of objects are usually clustered, an object smoothing model is adopted where a spatial smoothing constraint is imposed on its values during the estimation, and then it can be solved as a regularized matrix restoration problem with a spatial smoothing constraint. As a result, isolated noises can be suppressed while clustered foreground pixels can be preserved. We test our method on some challenging sequences and compare it with some other techniques. Experimental results show its effectiveness and robustness. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICME.2013.6607454 | ICME |
Keywords | Field | DocType |
video signal processing,pattern clustering,foreground estimation,2d images,smoothing methods,learning (artificial intelligence),subspace learning technique,foreground detection method,matrix algebra,regularized matrix restoration problem,object smoothing model,image denoising,isolated noises,background scenes,clustered foreground pixels,object detection,complex scenes,spatial smoothing constraint,background subspace learning,principal component analysis,learning artificial intelligence,vectors,mathematical model,noise | Computer vision,Object detection,Subspace topology,Pattern recognition,Matrix (mathematics),Computer science,Foreground detection,Robustness (computer science),Smoothing,Artificial intelligence,Image denoising,Pixel | Conference |
Volume | Issue | ISSN |
null | null | 1945-7871 |
Citations | PageRank | References |
3 | 0.38 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gengjian Xue | 1 | 82 | 5.89 |
| Li Song | 2 | 323 | 65.87 |
| Jun Sun | 3 | 76 | 11.28 |
| Jun Zhou | 4 | 42 | 4.57 |