Name
Abstract | ||
|---|---|---|
We address the problem of variational optical flow for video processing applications that need fast operation and robustness to drastic variations in illumination. Recently, a solution [1] has been proposed based on the photometric invariants of the dichromatic reflection model [2]. However, this solution is only applicable to colour videos with brightness variations. Greyscale videos, or colour videos with colour illumination changes cannot be adequately handled. We propose two illumination-robust variational methods based on cross-correlation that are applicable to colour and grey-level sequences and robust to brightness and colour illumination changes. First, we present a general implicit nonlinear scheme that assumes no particular analytical form of energy functional and can accommodate different image components and data metrics, including cross-correlation. We test the nonlinear scheme on standard synthetic data with artificial brightness and colour effects added and conclude that cross-correlation is robust to both kinds of illumination changes. Then we derive a fast linearised numerical scheme for cross-correlation based variational optical flow. We test the linearised algorithm on challenging data and compare it to a number of state-of-the-art variational flow methods. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.cviu.2010.07.006 | Computer Vision and Image Understanding |
Keywords | Field | DocType |
variational optical flow,state-of-the-art variational flow method,brightness variation,artificial brightness,illumination-robust variational optical flow,colour illumination change,illumination-robust variational method,colour video,illumination-robustness,illumination change,data metrics,cross-correlation,colour effect,synthetic data,video processing,cross correlation,variational method,optical flow | Computer vision,Video processing,Image processing,Robustness (computer science),Synthetic data,Artificial intelligence,Energy functional,Optical flow,Mathematics,Grayscale,Brightness | Journal |
Volume | Issue | ISSN |
114 | 10 | Computer Vision and Image Understanding |
Citations | PageRank | References |
15 | 0.67 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| József Molnár | 1 | 31 | 3.95 |
| Chetverikov, D. | 2 | 956 | 99.89 |
| Sándor Fazekas | 3 | 242 | 9.74 |