CAJ | 학술논문

针对复杂环境对运动目标检测与跟踪产生的不利影响,提出一种自适应运动能量阈值结合精简彩色SIFT描述子的特定运动目标检测与跟踪方法。运用自适应运动能量阈值方法自动滤除复杂环境干扰以完成运动目标检测,由此形成目标匹配搜索域,并给出经主成份分析及精简后的彩色SIFT描述子( PCA-CSIFT )进行目标匹配,从而实现特定运动目标的连续跟踪。实验结果表明,在复杂环境下,运动目标检测方法对目标总量变化不敏感,错误率始终稳定在6.5%~34%之间。 PCA-CSIFT算法在保持高可区分性的同时错误匹配率为25.33%~28%,平均每帧处理时间不超过0.26 s,具有较好的鲁棒性与实时性。
침대복잡배경대운동목표검측여근종산생적불리영향,제출일충자괄응운동능량역치결합정간채색SIFT묘술자적특정운동목표검측여근종방법。운용자괄응운동능량역치방법자동려제복잡배경간우이완성운동목표검측,유차형성목표필배수색역,병급출경주성빈분석급정간후적채색SIFT묘술자( PCA-CSIFT )진행목표필배,종이실현특정운동목표적련속근종。실험결과표명,재복잡배경하,운동목표검측방법대목표총량변화불민감,착오솔시종은정재6.5%~34%지간。 PCA-CSIFT산법재보지고가구분성적동시착오필배솔위25.33%~28%,평균매정처리시간불초과0.26 s,구유교호적로봉성여실시성。
Aiming at the disadvantageous affects caused by moving object detection and tracking in complex background of video scenes,a new method of detecting and tracking specific moving objects using adaptive moving energy threshold combined with compact colored SIFT descriptor is proposed. For detection of moving objects, disturbance of complex environment is filtered out automatically by adaptive moving energy threshold. Principal Components Analysis is applied to the Colored SIFT descriptor( PCA-CSIFT) for objects matching. Thereby the continuous tracking of specific moving objects is achieved. Extensive experiments on bench datasets show that,in complex background,the moving objects tracking method is not sensitive to the amount of objects and the ratio of error is stabilized at 6. 5% ~34%. The PCA-CSIFT holds high distinctiveness and robustness with ratio of mismatches 25. 33% ~28%. The average processing time of each frame is no more than 0. 26 s,so the method meets the need of real time.