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http://dx.doi.org/10.7471/ikeee.2019.23.1.207

Design and Implementation of Feature Detector for Object Tracking  

Lee, Du-hyeon (School of Electronics and Information Engineering, Korea Aerospace University)
Kim, Hyeon (School of Electronics and Information Engineering, Korea Aerospace University)
Cho, Jae-chan (School of Electronics and Information Engineering, Korea Aerospace University)
Jung, Yun-ho (School of Electronics and Information Engineering, Korea Aerospace University)
Publication Information
Journal of IKEEE / v.23, no.1, 2019 , pp. 207-213 More about this Journal
Abstract
In this paper, we propose a low-complexity feature detection algorithm for object tracking and present hardware architecture design and implementation results for real-time processing. The existing Shi-Tomasi algorithm shows good performance in object tracking applications, but has a high computational complexity. Therefore, we propose an efficient feature detection algorithm, which can reduce the operational complexity with the similar performance to Shi-Tomasi algorithm, and present its real-time implementation results. The proposed feature detector was implemented with 1,307 logic slices, 5 DSP 48s and 86.91Kbits memory with FPGA. In addition, it can support the real-time processing of 54fps at an operating frequency of 114MHz for $1920{\times}1080FHD$ images.
Keywords
computer vision; feature detection; FPGA; object tracking; Shi-Tomasi;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 G. Velez, O. Otaegui, "Embedding vision-based advanced driver assistance systems: a survey," IET Intelligent Transport Systems, vol. 11, no. 3, pp. 103-112, 2017. DOI: 10.1049/iet-its.2016.0026   DOI
2 A. Ferrick, J. Fish, E. Venator, G. S. Lee, "UAV Obstacle avoidance using image processing techniques," 2012 IEEE International Conference on Technologies for Practical Robot Applications, pp. 73-78, 2012. DOI: 10.1109/TePRA.2012.6215657
3 J. Lee, "Implementation of pedestrian recognition based on HOG using ROI for real time processing," Journal of IKEEE, vol. 18, no. 4, pp. 581-585, 2014. DOI: 10.7471/ikeee.2014.18.4.581   DOI
4 A. Smeulders, D. Chu et. al, "Visual tracking: an experimental survey," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 36, no. 7, pp. 1442-1468, 2014.   DOI
5 S. Kim, H. Kim, and S. Ko, "A vehicle detection and tracking algorithm for supervision of illegal parking," Journal of IKEEE, vol. 13, no. 2, pp. 232-240, 2009. DOI: 10.1109/TPAMI.2013.230
6 S. Smith and J. Bardy, "SUSAN-A new approach to low-level image processing," International Journal of Computer Vision, vol. 23, pp. 45-48, 1997. DOI: 10.1023/A:1007963824710   DOI
7 D. G. Lowe, "Distinctive image features from scales-invariant key points," International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2004. DOI: 10.1023/B:VISI.0000029664.99615.94   DOI
8 C. Harris and M. Stephens, "A combined corner and edge detector," Proceedings of the fourth alvey vision conference, pp. 147-151, 1988. DOI: 10.1.1.231.1604
9 W. Jang, S. O and G. Kim, "A hardware implementation of pyramidal KLT feature tracker for driving assistance systems," IEEE Conference on Intelligent Transportation Systems, pp. 220-225, 2009. DOI: 10.1109/ITSC.2009.5309680
10 T. Cho and K. Wong, "An efficient FPGA implementation of the Harris corner feature detector," 2015 IAPR International Conference of Machine Vision Application, 2015. DOI: 10.1109/MVA.2015.7153140
11 J. Shi and C. Tomasi, "Good features to track," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1994. DOI: 10.1109/CVPR.1994.323794
12 http://cvlab.hanyang.ac.kr/tracker_benchmark/benchmark_v10.html
13 T. Dinh et. al, "High throughput FPGA architecture for corner detection in traffic images," 2014 IEEE Fifth ICCE, pp. 297-302, 2014. DOI: 10.1109/CCE.2014.6916718
14 F. Brenot, P. Fillatreau and J. Piat, "FPGA based accelerator for visual features detection," 2015 IEEE International Workshop of CMSM, 2015. DOI: 10.1109/ECMSM.2015.7208697
15 A. Aguilar-Gonzalez, M. Arias-Estrada and F. Berry, "Robust feature extraction algorithm suitable for real-time embedded applications," Journal of Real-Time Image Processing, vol. 14, no. 3, pp. 647-665, 2018. DOI: 10.1007/s11554-017-0701-8   DOI