Abstract
In order to balance the accuracy and real-time performance of the moving target tracking system, an optimized design and implementation method based on high-level synthesis (HLS) of multi-feature fusion with kernel correlation filtering algorithms on FPGA is designed. This design improves the KCF algorithm with LBP and HOG features, and proposes a new dimensionality reduction method for LBP, which enhances the real-time performance while maintaining effective extraction of target features. The algorithm is implemented with FPGA, and a well acceleration effect is obtained on the basis of high precision. In test, the frame rate reaches 35 frames per second. Finally, it is verified through simulation that this feature extraction method can be used to process various image data such as infrared detection and SAR radar imaging, and has a wide range of applications.
Original language | English |
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Title of host publication | IET Conference Proceedings |
Publisher | Institution of Engineering and Technology |
Pages | 645-649 |
Number of pages | 5 |
Volume | 2020 |
Edition | 9 |
ISBN (Electronic) | 9781839535406 |
DOIs | |
Publication status | Published - 2020 |
Event | 5th IET International Radar Conference, IET IRC 2020 - Virtual, Online Duration: 4 Nov 2020 → 6 Nov 2020 |
Conference
Conference | 5th IET International Radar Conference, IET IRC 2020 |
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City | Virtual, Online |
Period | 4/11/20 → 6/11/20 |
Keywords
- FPGA
- KERNEL CORRELATION FILTER
- MUTI-FEATURE FUSION
- TARGET TRACKING