CAJ | 학술논문

针对已有视频分割算法对复杂动态背景下所出现的误分割问题,提出通过显著性映射构造时空注意特征,并采用分层条件随机场进行视频分割,提高分割准确率.算法首先根据视觉注意理论提取时域和空域特征,并建立加权混合模型.其次,采用该混合模型计算运动目标的显著性映射概率分布,有效地提取出运动目标区域.最后,在显著性映射概率分布基础上,采用高斯混合模型建立前景和背景的能量函数,构造分层条件随机场模型对这些特征能量函数进行分割建模,精确地提取出运动对象目标.实验结果表明,该算法即使对复杂动态背景下的视频也能够得到稳定的分割效果,有效地去除摄像机运动等所导致的误分割问题.
침대이유시빈분할산법대복잡동태배경하소출현적오분할문제,제출통과현저성영사구조시공주의특정,병채용분층조건수궤장진행시빈분할,제고분할준학솔.산법수선근거시각주의이론제취시역화공역특정,병건립가권혼합모형.기차,채용해혼합모형계산운동목표적현저성영사개솔분포,유효지제취출운동목표구역.최후,재현저성영사개솔분포기출상,채용고사혼합모형건립전경화배경적능량함수,구조분층조건수궤장모형대저사특정능량함수진행분할건모,정학지제취출운동대상목표.실험결과표명,해산법즉사대복잡동태배경하적시빈야능구득도은정적분할효과,유효지거제섭상궤운동등소도치적오분할문제.
To deal with the error segmentation problem of the existing video algorithms under complex and dynamic scenes,the Droposed method extracts spatial-temporal attention features with salient maps,and adopts hierarchical conditional random field for video segmentation.Firstly,the algorithm constructs a weighted combination model based on spatial-temporal features by using information theory.Then,it uses the defined model to compute probability distribution of salient maps,which can locate region of moving object effectively.Finally,the Gaussian mixture model is adopted to construct energy functions with the above probability distribution,and the hierarchical conditional random field is used to constraint these feature energy functions to refine final segmentation.The experiment results showed that the algorithm can avoid the error segmentation problem induced by camera movement. So it is robust to handle the videos under complex and dynamic scenes.