Name
Abstract | ||
|---|---|---|
The purpose of this study is to establish the tech- nique for estimating optical flow with high accuracy and robustness using gradient-based method with local optimization. To obtain high accuracy, we should understand error sources and how to reduce the errors. We proposed error reduction techniques for gradient measurement error which are a spatio- temporal median filter to reduce sensor noise and a spatio-temporal derivative filter to estimate gradi- ents of image function. The result shows that the spatio-temporal median filter can reduce the sensor noises very well, both of white noise and thermal noise of CCD camera. Furthermore, the best per- formance is achieved by the successive filtering of the Gussian filter and the spatio-temporal median filter. We also confirmed that estimation of par- tial derivatives of image function using the spatio- temporal derivative filter improved the accuracy of optical flow. The proposed methods are hopeful for the detection of optical flow with high accuracy and good robustness from image sequence. |
Year | Venue | Keywords |
|---|---|---|
1998 | MVA | thermal noise,ccd camera,optical flow,white noise,median filter,measurement error |
Field | DocType | Citations |
Computer vision,Root-raised-cosine filter,Median filter,Salt-and-pepper noise,Filter (signal processing),White noise,Adaptive filter,Kernel adaptive filter,Artificial intelligence,Mathematics,Filter design | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Atsushi Osa | 1 | 2 | 1.41 |
| Lin Zhang | 2 | 0 | 1.69 |
| Hidetoshi Miike | 3 | 68 | 12.05 |