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摘要:
The amount of computation for detecting moving objects by the optical flow algorithm is large. The optical flow information in the smooth region cannot be detected by the optical flow algorithm, and it is susceptible to noise in a complicated environment. In this study, an optimized Horn-Schunck (HS) optical flow algorithm based on motion estimation is proposed. To detect Harris corner in the image, the proposed algorithm is used in combination with the motion estimation algorithm based on macroblock to determine the region of interest (ROI) [1]. The ROI is then used as the initial motion vector for HS calculation to obtain the optical flow information. Filtering is conducted to eliminate the background noise. Experimental result shows that the application of the proposed algorithm improves the computational speed, avoids the interference of background noise, and enhances the robustness of HS. Moreover, the algorithm solves the problem rooted in the inability of the HS algorithm to detect the smooth part of optical flow information [2].
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篇名 Research on HS Optical Flow Algorithm Based on Motion Estimation Optimization
来源期刊 电脑和通信(英文) 学科 工学
关键词 MOTION ESTIMATION HS Optical FLOW MACROBLOCK REGION of INTEREST
年,卷(期) 2018,(11) 所属期刊栏目
研究方向 页码范围 171-184
页数 14页 分类号 TP39
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MOTION
ESTIMATION
HS
Optical
FLOW
MACROBLOCK
REGION
of
INTEREST
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研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
电脑和通信(英文)
月刊
2327-5219
武汉市江夏区汤逊湖北路38号光谷总部空间
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783
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0
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