A PSO/HS based algorithm for optimization tasks

Ülker, Ezgi Deniz

doi:10.1109/sai.2017.8252090

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…Using the previous frame image as the background model of the current frame has a good real-time performance because the time interval among adjacent frames is short. Its background is not accumulated [6], and the update speed is fast. The algorithm is simple, and the computation amount is small.…”

Section: Frame Difference Methodsmentioning

confidence: 99%

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Research on HS Optical Flow Algorithm Based on Motion Estimation Optimization

Wei¹,

Zou²,

Bo³

et al. 2018

JCC

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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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Section: Frame Difference Methodsmentioning

confidence: 99%

“…x y adjacent area, and K refers to the times of iteration. Formulas (6) and (7) imply that the amount of computation of the HS optical flow equation depends on the iteration. When the initial value is close to the real value, the convergence of iteration is fast.…”

Section: Suppose ( )mentioning

confidence: 99%