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http://dx.doi.org/10.6109/jkiice.2021.25.7.962

Vision-based Real-time Vehicle Detection and Tracking Algorithm for Forward Collision Warning  

Hong, Sunghoon (CARNAVICOM)
Park, Daejin (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.7, 2021 , pp. 962-970 More about this Journal
Abstract
The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.
Keywords
Advanced driver assistance systems; Forward collision warning system; Object detection; Low-power vision processing;
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1 P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. 511-518, 2001. doi: 10.1109/CVPR.2001.990517.
2 S. Zhang and L. Su, "A New Fast Matching Algorithm for Angle-Adaptive Grayscale Templates," 2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM), pp. 672-675, 2019. doi: 10.1109/WCMEIM48965.2019.00142.   DOI
3 S. Zhang, L. Chai, and L. Jin, "Vehicle Detection in UAV Aerial Images Based on Improved YOLOv3," 2020 IEEE International Conference on Networking, Sensing and Control (ICNSC), pp. 1-6, 2020. doi: 10.1109/ICNSC48988.2020.9238059.   DOI
4 M. A. Zulkhairi, Y. M. Mustafah, Z. Z. Abidin, H. F. M. Zaki, and H. A. Rahman, "Car Detection Using Cascade Classifier on Embedded Platform," 2019 7th International Conference on Mechatronics Engineering (ICOM), pp. 1-3, 2019. doi: 10.1109/ICOM47790.2019.8952064.   DOI
5 K. Chang and C. Fan, "Cost-Efficient Adaboost-based Face Detection with FPGA Hardware Accelerator," 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW), pp. 1-2, 2019. doi: 10.1109/ICCE-TW46550. 2019.8991862.   DOI
6 NXP Layerscape LS1028A Family of Industrial Applications Processors [Internet]. Available: https://www.nxp.com/docs/en/fact-sheet/LS1028AFS.pdf.
7 W. Lee and C. Chen, "A Fast Template Matching Method With Rotation Invariance by Combining the Circular Projection Transform Process and Bounded Partial Correlation," in IEEE Signal Processing Letters, vol. 19, no. 11, pp. 737-740, Nov. 2012. doi: 10.1109/LSP.2012.2212010.   DOI
8 Z. Hao, Q. Feng, and L. Kaidong, "An Optimized Face Detection Based on Adaboost Algorithm," 2018 International Conference on Information Systems and Computer Aided Education (ICISCAE), pp. 375-378, 2018. doi: 10.1109/ICISCAE.2018.8666925.   DOI
9 C. Zhang, G. Liu, X. Zhu, and H. Cai, "Face Detection Algorithm Based on Improved AdaBoost and New Haar Features," 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), pp. 1-5, 2019. doi: 10.1109/CISP-BMEI48845.2019.8965841.   DOI
10 S. A. Nur, M. M. Ibrahim, N. M. Ali, and F. I. Y. Nur, "Vehicle detection based on underneath vehicle shadow using edge features," 2016 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), pp. 407-412, 2016. doi: 10.1109/ICCSCE.2016.7893608.   DOI