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DOI: 10.14569/IJACSA.2018.091053
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Zynq FPGA based and Optimized Design of Points of Interest Detection and Tracking in Moving Images for Mobility System

Author 1: Abdelkader BEN AMARA
Author 2: Mohamed ATRI
Author 3: Edwige PISSALOUX
Author 4: Richard GRISEL

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 10, 2018.

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Abstract: In this paper, an FPGA based mobile feature detection and tracking solution is proposed for complex video processing systems. Presented algorithms include feature (corner) detection and robust memory allocation solution to track in real-time corners using the extended Kalman filter. Target implementation environment is a Xilinx Zynq SoC FPGA based. Using the HW/SW partitioning flexibility of Zynq, the ARM dual core processor performance and hardware accelerators generated by Xilinx SDSOC and Vivado HLS tools improve the system ability of processing video accurately with a high frame rate. Several original innovations allow to improve the processing time of the whole system (detection and tracking) by 50% as shown in experimental validation (tracking of visually impaired during their outdoor navigation).

Keywords: Feature detection; harris & stephens corner detector; tracking; extended kalman filter; HW/SW partitionning; zynq SoC; computer vision; memory access; ARM A9; HLS; Interlacing; blancking; progressive video

Abdelkader BEN AMARA, Mohamed ATRI, Edwige PISSALOUX and Richard GRISEL, “Zynq FPGA based and Optimized Design of Points of Interest Detection and Tracking in Moving Images for Mobility System” International Journal of Advanced Computer Science and Applications(IJACSA), 9(10), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091053

@article{AMARA2018,
title = {Zynq FPGA based and Optimized Design of Points of Interest Detection and Tracking in Moving Images for Mobility System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091053},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091053},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {10},
author = {Abdelkader BEN AMARA and Mohamed ATRI and Edwige PISSALOUX and Richard GRISEL}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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