Name
Abstract | ||
|---|---|---|
An accurate real-time motion sensor implemented in an FPGA is introduced in this paper. This sensor applies an optical flow algorithm based on ridge regression to solve the collinear problem existing in traditional least squares methods. It additionally applies extensive temporal smoothing of the image sequence derivatives to improve the accuracy of its optical flow estimates, Implemented on a customized embedded FPGA platform, it is capable of processing 60 320 x 240 images or 15 640x480 images per second By evaluating its accuracy on synthetic sequences, it is shown here that the proposed design achieves very high accuracy compared to other known hardware based designs. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICPR.2008.4761126 | 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 |
Keywords | Field | DocType |
least square method,ridge regression,real time,accuracy,adaptive optics,optical flow,fpga,computer vision,field programmable gate arrays,optical imaging | Least squares,Computer vision,Computer science,Field-programmable gate array,Smoothing,Motion sensors,Artificial intelligence,Optical flow,Optical imaging,Image sequence,Adaptive optics | Conference |
ISSN | Citations | PageRank |
1051-4651 | 7 | 0.64 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhaoyi Wei | 1 | 122 | 9.18 |
| Dah-Jye Lee | 2 | 422 | 42.05 |
| Brent E. Nelson | 3 | 616 | 79.91 |
| James K. Archibald | 4 | 632 | 161.01 |