CAJ | 학술논문

提出了一种静止摄像机条件下自适应的运动目标检测方法.该方法基于同一像素点被同一灰度车辆覆盖几率小的假设构建初始背景,为每个像素点在线选择高斯分布个数.根据像素点与其邻域像素间存在联系的思想,在线更新学习率.最后用背景差分法检测出运动目标.实验结果表明,同基于传统混合高斯模型的运动目标检测方法相比,该方法有较好的自适应性,能快速适应场景的变化.
제출료일충정지섭상궤조건하자괄응적운동목표검측방법.해방법기우동일상소점피동일회도차량복개궤솔소적가설구건초시배경,위매개상소점재선선택고사분포개수.근거상소점여기린역상소간존재련계적사상,재선경신학습솔.최후용배경차분법검측출운동목표.실험결과표명,동기우전통혼합고사모형적운동목표검측방법상비,해방법유교호적자괄응성,능쾌속괄응장경적변화.
An adaptive approach to detect moving objects with a static camera was proposed in this paper. Based on the assumption that the probability of the same pixel covered by the same intensity of the car is the least,the initial background was established and the number of Gaussians for each pixel on-line was chosen. In order to update the Gaussians parameters,the learning rate should be updated on-line according to the relationship between the pixel and its adjacent pixels. Lastly,the moving objects were detected by background subtraction. Compared to the moving objects detection approach based on conventional mixture Gaussian model,this approach has preferable adaptive performance,and can deal with changes in scenes rapidly.