To improve the real-time image acquisition and stabilization ability of dynamic robotic dog video acquisition devices, a dynamic robotic dog video image stabilization algorithm based on local low-rank regularization is proposed. Firstly, by studying the image acquisition system of a dynamic robotic dog video acquisition device, a real-time image acquisition and stabilization algorithm suitable for this system was developed based on the prior knowledge of motion morphology components. Then, the rolling curtain effect of the loading video capture device was eliminated through the principle of grid. These results confirmed that the improved algorithm achieved stable performance with approximate Gaussian weights between 170 frames and 230 frames, with the highest ITF value at $\tau =1$ and an average IFT value of 33.42 after 20 iterations. Then, $r=30$ , $\beta =1000$ , and $\omega _{2}$ were selected as the default parameters. The average cropping rate of the improved algorithm was only 0.61, the average distortion was 0.42, and the average stability was 0.69. The improved algorithm scored 3.33 in the “crowd” category of videos, ranking first. After verification, the real-time image acquisition and stabilization algorithm designed by the research institute had good real-time performance and stability. It can meet the real-time image acquisition and stabilization requirements of dynamic robotic dog video acquisition devices.
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