CAJ | 학술논문

在预警系统和目标记录方面，传统的视频跟踪方法无法很好地解决目标重现和遮挡等问题，针对此类问题提出了一种融合多特征的视频目标跟踪方法，首先用背景建模的方法检测运动前景，分离目标图像，通过目标连续帧间的位移信息实现跟踪，对多目标帧间位移相近的情况，融合目标SIFT和彩色直方图特征进行目标匹配，并记录目标各帧的运动状态，最终实现目标运动的跟踪。实验结果表明，该方法对多目标缓慢变化的监控视频有较好的跟踪效果。
재예경계통화목표기록방면，전통적시빈근종방법무법흔호지해결목표중현화차당등문제，침대차류문제제출료일충융합다특정적시빈목표근종방법，수선용배경건모적방법검측운동전경，분리목표도상，통과목표련속정간적위이신식실현근종，대다목표정간위이상근적정황，융합목표SIFT화채색직방도특정진행목표필배，병기록목표각정적운동상태，최종실현목표운동적근종。실험결과표명，해방법대다목표완만변화적감공시빈유교호적근종효과。
Video tracking is a vital technique for the application of intelligent video surveillance. In terms of pre-warning systems and event recording, traditional video tracking methods cannot solve the problems of object reap-pearance and shadows very well. To tackle these problems, a video tracking method based on object multi-feature fusion is proposed. Firstly, the foreground of a moving target was detected using the method of background model-ing, and the image of the moving target was separated from the video frame. Then the target that had been detected currently was set to match the target that appeared previously through the location information of the sequential frames of the object. Furthermore, considering the failure of the location matching, the SIFT( scale invariant feature transform ) and color histogram feature of the target image were extracted to match the different targets. The experi-mental results showed excellent performance of the real-time video tracking of multi-objects moving slowly in the general surveillance system.