Name
Abstract | ||
|---|---|---|
Real-time stereo vision has proven to be a useful technology with many applications. However, the computationally intensive nature of stereo vision algorithms makes real-time implementation difficult in resource-limited systems. The field-programmable gate array (FPGA) has proven to be very useful in the implementation of local stereo methods, yet the resource requirements can still be a significant challenge. This paper proposes a variety of sparse census transforms that dramatically reduce the resource requirements of census-based stereo systems while maintaining stereo correlation accuracy. This paper also proposes and analyzes a new class of census-like transforms, called the generalized census transforms. This new transform allows a variety of very sparse census-like stereo correlation algorithms to be implemented while demonstrating increased robustness and flexibility. The resource savings and performance of these transforms is demonstrated by the design and implementation of a parameterizable stereo system that can implement stereo correlation using any census transform. Several optimizations for typical FPGA-based correlation systems are also proposed. The resulting system is capable of running at over 500 MHz on a modern FPGA, resulting in a throughput of over 500 million input pixel pairs per second. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TCSVT.2012.2203197 | IEEE Trans. Circuits Syst. Video Techn. |
Keywords | Field | DocType |
field programmable gate arrays,stereo image processing,transforms,FPGA,field programmable gate array,generalized census transforms,real time stereo vision,resource optimized stereo vision,resource savings,sparse census transforms,stereo correlation accuracy,stereo correlation algorithms,Census transform,field-programmable gate array (FPGA),generalized census,sparse census,stereo vision | Computer vision,Stereopsis,Computer science,Field-programmable gate array,Robustness (computer science),Census transform,Gate array,Artificial intelligence,Pixel,Throughput,Computer stereo vision | Journal |
Volume | Issue | ISSN |
23 | 1 | 1051-8215 |
Citations | PageRank | References |
9 | 0.52 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wade S. Fife | 1 | 23 | 1.36 |
| James K. Archibald | 2 | 632 | 161.01 |