CAJ | 학술논문

基于非刚性目标运动跟踪问题进行分析，针对运动过程中目标会出现旋转、比例变化及形变等情况，在复杂的背景中通过特征识别匹配实现跟踪。以运动目标的检测识别方法及特征识别方法为出发点，对目前几种经典方法进行分析、比较。结果表明：与光流法及背景差分法相比，MGI 在非刚性目标运动的检测准确率、实时性以及鲁棒性方面均占优势；特征匹配技术SURF 则可更好地平衡处理速度和效果性能。以 SIFT 使用不同尺度确定稳定特征点的思路为基础，提出多小波变换图像分析方法，用于实现对序列图像运动目标的特征匹配。
기우비강성목표운동근종문제진행분석，침대운동과정중목표회출현선전、비례변화급형변등정황，재복잡적배경중통과특정식별필배실현근종。이운동목표적검측식별방법급특정식별방법위출발점，대목전궤충경전방법진행분석、비교。결과표명：여광류법급배경차분법상비，MGI 재비강성목표운동적검측준학솔、실시성이급로봉성방면균점우세；특정필배기술SURF 칙가경호지평형처리속도화효과성능。이 SIFT 사용불동척도학정은정특정점적사로위기출，제출다소파변환도상분석방법，용우실현대서렬도상운동목표적특정필배。
The analysis based on non-rigid object motion tracking. In a complex background by the feature,we identified the tracking match through the goal conditions of rotation,scaling and deforma-tion changes in the campaign course. The starting point was to analyze the detection and identification method and feature recognition method of moving targets and to comparatively analyze on the current development of several classical methods. Compared with the optical flow method and background subtraction,MGI has advantages in non-rigid object motion detection accuracy,timeliness and robust-ness dominant. Feature matching technology,SURF can better balance processing speed and effec-tiveness of performance. Based on the idea of the SIFT of different scales to determine the stability feature points,we proposed multi-wavelet transform image analysis,which was used to implement the feature match of image sequences moving targets.