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Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device
| Content Provider | Semantic Scholar |
|---|---|
| Author | Yu, Zheqi Yang, Shufan Sillitoe, Ian P. W. Buckley, Kevan |
| Copyright Year | 2017 |
| Abstract | Currently, most designers face a daunting task to research different design flows and learn the intricacies of specific software from various manufacturers in hardware/software co-design. An urgent need of creating a scalable hardware/software co-design platform has become a key strategic element for developing hardware/software integrated systems. In this paper, we propose a new design flow for building a scalable co-design platform on FPGA-based system-on-chip. We employ an integrated approach to implement a histogram oriented gradients (HOG) and a support vector machine (SVM) classification on a programmable device for pedestrian tracking. Not only was hardware resource analysis reported, but the precision and success rates of pedestrian tracking on nine open access image data sets are also analysed. Finally, our proposed design flow can be used for any real-time image processing-related products on programmable ZYNQ-based embedded systems, which benefits from a reduced design time and provide a scalable solution for embedded image processing products. |
| Starting Page | 127 |
| Ending Page | 132 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| DOI | 10.1109/icce-asia.2017.8307853 |
| Alternate Webpage(s) | http://eprints.gla.ac.uk/147371/7/147371.pdf |
| Alternate Webpage(s) | https://doi.org/10.1109/icce-asia.2017.8307853 |
| Journal | 2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
