Name
Abstract | ||
|---|---|---|
Foreground extraction is a fundamental step of video analysis. The common solution for foreground extraction is background subtraction which is based on color information. However, color is sensitive to intensity changes and may lose efficacy in complex scenes such as scene with low contrast or strong illumination. To overcome the disadvantages of color-based methods, we propose a new approach based on edge information. We get the edge of foreground from color-based background instead of edge-based background to reduce calculation amount. And a novel multi-resolution edge aggregation algorithm is used to solve the edge-filling problem, especially in the case when edge is not continuous. This algorithm obtains foreground region through expands the influence of the edges and reduces the gaps between the edges. Both visual and quantitative comparisons on various image sequences validate the efficacy of our method. © Springer International Publishing Switzerland 2015. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-21978-3_8 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
Edge aggregation,Foreground extraction,Multi-resolution | Background subtraction,Computer vision,Pattern recognition,Computer science,Algorithm,Artificial intelligence | Conference |
Volume | ISSN | ISBN |
9217 | 03029743 | 9783319219776 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhu Wenqian | 1 | 1 | 1.03 |
| Baobing Wang | 2 | 58 | 12.69 |
| Hu Xuefeng | 3 | 3 | 1.43 |
| Zhao Yong | 4 | 90 | 14.85 |