Name
Abstract | ||
|---|---|---|
Coherent image regions can be used as good features for many computer vision tasks, such as object tracking, segmentation, and recognition. Most of previous region extraction methods, however, are not suitable for online applications because of their either heavy computations or unsatisfactory results. We propose a seed-based region growing and merging approach to generate simultaneously coherent ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSVT.2016.2615466 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | Field | DocType |
Feature extraction,Image segmentation,Merging,Object tracking,Pipelines,Image edge detection,Time complexity | Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation-based object categorization,Feature extraction,Image segmentation,Video tracking,Region growing,Artificial intelligence,Initialization,Quadtree | Journal |
Volume | Issue | ISSN |
28 | 3 | 1051-8215 |
Citations | PageRank | References |
0 | 0.34 | 47 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junliang Xing | 1 | 1193 | 63.31 |
| Weiming Hu | 2 | 5300 | 261.38 |
| Haizhou Ai | 3 | 1742 | 116.51 |
| Shuicheng Yan | 4 | 767 | 25.71 |