To enhance the effect of motion detection, a Gaussian modeling algorithm is proposed to fix holes and breaks caused by the conventional frame difference method. The proposed algorithm uses an improved three-frame difference method. A three-frame image sequence with one frame interval is selected for pairwise difference calculation. The logical “OR” operation is used to achieve fast motion detection and to reduce voids and fractures. The Gaussian algorithm establishes an adaptive learning model to make the size and contour of the motion detection more accurate. The motion extracted by the improved three-frame difference method and Gaussian model is logically summed to obtain the final motion foreground picture. Moreover, a moving target detection method, based on the U-Net deep learning network, is proposed to reduce the dependency of deep learning on the number of training datasets. It helps the algorithm to train models on small datasets. Next, it calculates the ratio of the number of positive and negative samples in the dataset and uses the reciprocal of the ratio as the sample weight to deal with the imbalance of positive and negative samples. Finally, a threshold is set to predict the results for obtaining the moving object detection accuracy. Experimental results show that the algorithm can suppress the generation and rupture of holes and reduce the noise. Also, it can quickly and accurately detect movement to meet the design requirements.

中文翻译：

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三帧差分法的深度学习驱动的高斯建模和改进的运动检测算法

为了增强运动检测的效果，提出了一种高斯建模算法来修复传统帧差方法造成的空洞和中断。该算法采用改进的三帧差分法。选择具有一帧间隔的三帧图像序列进行成对差异计算。逻辑“或”操作用于实现快速运动检测并减少空隙和裂缝。高斯算法建立自适应学习模型，使运动检测的大小和轮廓更加准确。将改进的三帧差分法和高斯模型提取的运动进行逻辑相加，得到最终的运动前景画面。此外，一种基于U-Net深度学习网络的运动目标检测方法，建议减少深度学习对训练数据集数量的依赖。它有助于算法在小数据集上训练模型。接下来计算数据集中正负样本数的比例，并以该比例的倒数作为样本权重来处理正负样本的不平衡。最后，设置一个阈值来预测结果以获得运动物体检测精度。实验结果表明，该算法能够抑制孔洞的产生和破裂，降低噪声。此外，它可以快速准确地检测运动，以满足设计要求。它计算数据集中正负样本数的比率，并以比率的倒数作为样本权重来处理正负样本的不平衡。最后，设置一个阈值来预测结果以获得运动物体检测精度。实验结果表明，该算法能够抑制孔洞的产生和破裂，降低噪声。此外，它可以快速准确地检测运动，以满足设计要求。它计算数据集中正负样本数的比率，并以比率的倒数作为样本权重来处理正负样本的不平衡。最后，设置阈值来预测结果以获得运动物体检测精度。实验结果表明，该算法能够抑制孔洞的产生和破裂，降低噪声。此外，它可以快速准确地检测运动，以满足设计要求。