运动目标检测中的环境感知与自适应研究

Environmental perception and adaptive research in moving object detection

在复杂环境下,任何环境的改变都会对运动目标检测的准确性产生影响。因此提出广义高斯混合模型与背景减除法相结合的算法对运动目标进行检测。该模型可以灵活地感知环境,自适应地处理视频背景模型中背景的环境变化,如光线渐变、背景扰动、阴影和噪声等,而且当光线突变时可以迅速感知并重新建模。此外为了满足实时性,采取每隔3帧进行一次背景更新的策略。实验结果证明本算法在满足实时性的同时,能准确检测出运动目标。

In complicated environment,any changes will influence the accuracy of the object detection.Therefore,an algorithm was put forward,which combined the Generalized Gaussian Mixture Model（GGMM） and background subtraction to detect moving objects.The model has a flexibility to perceive environment and model the video background adaptively in the presence of environmental changes（such as radial gradient,background disturbance,shadows and noise）.And when it has sudden illumination change,the model can resolve it quickly.In order to meet the real-time requirement,this algorithm adopted the principle,to update every other two frames.The experiments show that it can meet the real-time requirement and detect the moving object accurately.