In order to achieve accurate detection of moving objects in video images, the idea of constructing low-rank sparse matrix decomposition algorithm was used to detect moving objects in video images. The low rank sparse matrix decomposition algorithm was applied to detect moving objects in video images, and then the stability, accuracy, image extraction, restoration, error, work efficiency and other aspects of the algorithm were compared with traditional algorithms and analyzed. The results showed that the low rank sparse matrix decomposition algorithm had obvious advantages over the traditional algorithm in terms of stability. The standard deviation of the algorithm in this research was 0.011 and that of the traditional algorithm was 0.024. The algorithm in this paper also has good performance in terms of detection accuracy and error. The detection accuracy can reach 93.7%, while that of the traditional algorithm is only 79.6%. In addition, the low rank sparse matrix decomposition algorithm has no shadow on the extraction and restoration of moving images. Compared with the traditional algorithm, the computational efficiency of the algorithm in this paper is improved by 37.8%. The algorithm in this paper has no difference in the detection results of moving objects or people in video images. Based on the low rank sparse matrix decomposition algorithm, the operation of the algorithm was discussed through precise detection of moving objects in video images. The algorithm presented in this paper shows a very comprehensive outstanding result, and also shows that the efficient and normal operation of the algorithm is a comprehensive result, which requires a good operation situation of multiple. This study greatly improves the understanding of low rank sparse matrix decomposition algorithm and moving target detection.