Name
Abstract | ||
|---|---|---|
Stable video has a significant effect on video based traffic parameters extraction system. This paper proposed a fast video stabilization method based on feature matching and histogram clustering. Firstly, the method extract ORB feature points on sub-images which are set in adjacent frames and then matches them based on Hamming Distance. Secondly, the motion consistency principle combined with histogram clustering is used to get correct matches which can be used to calculate the parameters of the affine transformation matrix. Finally, after filtering those parameters, stable frame can be obtained by warping the original frame using the affine transformation matrix. Experimental results show that the proposed method can effectively stabilize videos with low complexity in real time. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-38771-0_31 | INFORMATION TECHNOLOGY AND INTELLIGENT TRANSPORTATION SYSTEMS, VOL 2 |
Keywords | DocType | Volume |
Video stabilization,Motion estimation,Feature matching,Histogram clustering | Conference | 455 |
ISSN | Citations | PageRank |
2194-5357 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baotong Li | 1 | 0 | 0.34 |
| Yangzhou Chen | 2 | 80 | 17.17 |
| Jianqiang Ren | 3 | 49 | 9.27 |
| Lan Cheng | 4 | 0 | 0.34 |