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- W4383748017 abstract "A target detection-based autofocus system is built to address the problem of unreasonable focus window planning in today's autofocus systems. A window planning strategy based on the HOG+SVM algorithm and an improved hill-climbing search algorithm are proposed for pedestrian targets. The two algorithms are validated separately, and the results show that the new window planning strategy improves the focusing accuracy and anti-interference ability of the system, so that the system will not be interfered by the background and occlusion when focusing on the target; the improved hill-climbing search algorithm adopts the way of recording first and then comparing to reduce the influence of local peaks. The experimental results prove that the focusing accuracy of the system is above 95% and the average running time is about 2.2s, which meets the demand of auto-focusing." @default.
- W4383748017 created "2023-07-11" @default.
- W4383748017 creator A5033353597 @default.
- W4383748017 date "2023-05-12" @default.
- W4383748017 modified "2023-09-27" @default.
- W4383748017 title "Research on target detection-based autofocus system" @default.
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- W4383748017 doi "https://doi.org/10.1109/cvidl58838.2023.10166324" @default.
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