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Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device

Yu, wZheqi; Yang, Shufan; Sillitoe, Ian; Buckley, Kevan


wZheqi Yu

Ian Sillitoe

Kevan Buckley


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.

Presentation Conference Type Conference Paper (Published)
Conference Name 2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)
Start Date Oct 5, 2017
End Date Oct 7, 2017
Online Publication Date Mar 8, 2018
Publication Date 2018
Deposit Date Mar 12, 2021
Publisher Institute of Electrical and Electronics Engineers
ISBN 9781538627877
Public URL