An FPGA-oriented Graph Cut Algorithm for Accelerating Stereo Vision
| Autor: | Kiyoshi Oguri, Ryo Kamasaka, Yuichiro Shibata |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Speedup
business.industry Computer science 020208 electrical & electronic engineering Clock rate ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Field (computer science) Computational science Software Stereopsis Cut 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business Lattice graph Field-programmable gate array |
| Zdroj: | ReConFig |
| DOI: | 10.1109/reconfig.2018.8641737 |
| Popis: | Stereo vision, which reconstructs 3-D information from images obtained by two cameras, is one of the topics most actively addressed in the field of computer vision. While the stereo vision problem can be formulated and solved as an energy minimization problem such as a graph cut, the embedded implementation for real-time systems is difficult due to high computational intensity. This paper proposes a novel parallel-processing-friendly graph cut algorithm and its FPGA implementation for accelerating stereo vision, in which object surfaces are estimated by solving a min-cut problem of a 3-D grid graph. In the proposed algorithm, node-wise parallelism is actively extracted by introducing a concept of wave propagation. The implementation experiments reveal that a system for 12 x 12 x 7-node graphs can be implemented on a single FPGA and works at the clock frequency of 100 MHz. In this case, the system achieves 166 times speedup compared to CPU execution of a common software library of a graph cut. |
| Databáze: | OpenAIRE |
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