EOG-DS:动态目标变焦双光跟踪算法

EOG-DS:Zoom Dual-Mode Tracking Algorithm for Dynamic Targets

配置大倍率光学系统的双光复合跟踪在地面空中监视取证等领域有广泛的应用。目前基于图像的目标跟踪算法研究主要是单光跟踪,在双光图像跟踪算法,特别是动态变焦过程中图像跟踪方面缺乏深入研究。针对双光跟踪视场变焦时的图像模糊、尺度快速变化容易导致目标丢失的问题,提出基于Dempster-Shafer(DS)理论的动态目标变焦双光跟踪算法。通过DS决策级融合可见光与红外跟踪目标响应图,利用双光互补优势综合判断目标位置,实现大小视场的复合跟踪;实时检测可见光和红外图像目标的能量梯度(energy of gradient,EOG),在融合中引入模糊度信息,提高图像变焦模糊的适应性。通过双光大小视场尺度归一化的处理避免尺度快速变化导致的跟丢问题。实验结果表明,提出的EOG-DS融合跟踪算法提高了跟踪的稳定性,跟踪精确率为0.833,成功率为0.41,均有明显提升,跟踪速率达到26.87 FPS,满足实时性要求。

Dual-mode fusion tracking with high magnification optical system is widely used in ground air surveillance and forensics.The research of image-based target tracking algorithm is mainly single-mode,but there is a lack of in-depth research on dual-mode,image tracking algorithm,especially in the process of dynamic zoom.To solve the problem that the target is easily lost due to blurred image and the rapid change of scale in dual-mode tracking,a dynamic target zoom dual-mode tracking algorithm based on DS theory is proposed.Through the fusion of visible and infrared tracking target response map at DS decision level,the target position is comprehensively judged by the complementary advantages of dual-mode,and the fusion tracking of large and small field of view is realized.The EOG of visible and infrared image is detected in real time,and the blur information is introduced into the fusion to improve the adaptability of image zoom blur.The tracking problem caused by the rapid change of the scale is avoided by the normalization of the field of view of dual-mode size.The experimental results show that the proposed EOG-DS fusion tracking algorithm improves the stability of tracking,the tracking accuracy is 0.833,the success rate is 0.41,and the tracking rate reaches 26.87 FPS,which meets the real-time requirements.