CAJ | 학술논문

为了实现对变尺度快速运动目标的良好跟踪，在对传统 Mean Shift跟踪算法改进的基础上，提出了一种运动目标自适应跟踪算法。该算法首先采用目标区域的像素点空域加权后的彩色图像作为初始帧目标模板，目标的真实位置利用 Mean Shift算法迭代求得，从而实现对快速运动目标的空间定位，然后将相邻帧的目标采用尺度不变特征变换(SIFT)算子进行特征匹配，根据目标的缩放因子实时更新下一帧的核带宽，修正算法跟踪窗口的尺寸，以适应目标尺度的变化，从而实现对快速运动目标的尺度定位。最后，通过实验表明，与传统的 Mean Shift跟踪算法相比，该算法的跟踪准确率达到97%以上，能够实现对变尺度快速运动目标的精确跟踪。
위료실현대변척도쾌속운동목표적량호근종，재대전통 Mean Shift근종산법개진적기출상，제출료일충운동목표자괄응근종산법。해산법수선채용목표구역적상소점공역가권후적채색도상작위초시정목표모판，목표적진실위치이용 Mean Shift산법질대구득，종이실현대쾌속운동목표적공간정위，연후장상린정적목표채용척도불변특정변환(SIFT)산자진행특정필배，근거목표적축방인자실시경신하일정적핵대관，수정산법근종창구적척촌，이괄응목표척도적변화，종이실현대쾌속운동목표적척도정위。최후，통과실험표명，여전통적 Mean Shift근종산법상비，해산법적근종준학솔체도97%이상，능구실현대변척도쾌속운동목표적정학근종。
An auto-adaptive tracking algorithm for fast moving target is put forward based on the improved traditional Mean Shift tracking algorithm, in order to achieve good tracking of fast moving target with variable scale. This algorithm firstly adopts the color image constituted by the pixels of target region with spatial weighting as initial frame object template, and the true position of target is obtained by the iteration of Mean Shift algorithm, therefore the spatial localization of fast moving target is realized. Then the features of adjacent frame targets are matched by Scale Invariant Feature Transform(SIFT) operator;the kernel bandwidth of next frame is updated in real time according to the scaling factor of target; the tracking window size of the algorithm is amended, which can adapt to the variable scales of the target, so the scale localization of fast moving target is achieved. Finally, the experiments demonstrate that compared with the traditional Mean Shift tracking algorithm, the tracking accuracy rate of the algorithm is above 97%, and the algorithm can accurately track the fast moving target with variable scales.