Name
Abstract | ||
|---|---|---|
Optical flow computation has been extensively used for motion estimation of objects in image sequences. The results obtained
by most optical flow techniques are computationally intensive due to the large amount of data involved. A new change-based
data flow pipelined architecture has been developed implementing the Horn and Schunk smoothness constraint; pixels of the
image sequence that significantly change, fire the execution of the operations related to the image processing algorithm.
This strategy reduces the data and, combined with the custom hardware implemented, it achieves a significant optical flow
computation speed-up with no loss of accuracy. This paper presents the bases of the change-driven data flow image processing
strategy, as well as the implementation of custom hardware developed using an Altera Stratix PCI development board. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s11554-007-0060-y | J. Real-Time Image Processing |
Keywords | Field | DocType |
motion estimation,image processing,data flow,optical flow | Stratix,Computer vision,Architecture,Computer science,Image processing,Artificial intelligence,Pixel,Motion estimation,Smoothness,Optical flow,Data flow diagram | Journal |
Volume | Issue | ISSN |
2 | 4 | 1861-8219 |
Citations | PageRank | References |
6 | 0.48 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julio C. Sosa | 1 | 11 | 1.61 |
| Jose Antonio Boluda | 2 | 11 | 1.97 |
| F. Pardo | 3 | 82 | 11.00 |
| Rocío Gómez-Fabela | 4 | 10 | 0.89 |