基于自适应学习率的运动目标高效检测算法

High-Efficiency Detection Algorithm for Moving Targets Based on Adaptive Learning Rate

该文提出了一种改进的基于自适应学习率高斯建模的三帧差分算法。通过基于自适应学习率的混合高斯背景建模,实现背景模型的自适应修正,保证算法在动态环境中能完整提取目标内部信息。其次,采用基于边缘提取的三帧差分改进算法,完成对目标轮廓的快速提取,并以此作为目标图像的边缘补充。实验结果表明,该算法能够完整提取运动目标,并保证目标边缘的连续与平滑,同时检测的速度得到提升,可广泛应用于智能监控、医疗等领域。

This paper proposes a three-frame difference method based on adaptive learning rate Gaussian mixture modeling. Through the Gaussian mixture background modeling based on adaptive learning rate, the adaptive correction of the background model is realized, and the algorithm can completely extract the internal information of the target in the dynamic environment. Then, the three-frame difference improvement algorithm based on edge extraction is used to extract the target contour rapidly and use it as the edge complement. The experimental results show that the algorithm can completely extract moving targets and ensure the continuity and smoothness of the target edges. At the same time, the speed of target detection is increased, and it can be widely used in intelligent video surveillance, medical treatment and other fields.