针对基于压缩感知的目标跟踪算法在跟踪过程中,光照剧烈变化引起跟踪不稳定或跟踪失败的问题, 本文提出了一种基于相位一致性的改进跟踪方法.该方法利用相位一致性图像特征对光照变化不敏感的特点, 首先对样本搜索区域内的图像进行相位一致性变换, 然后再提取变换后相位一致性图像的特征,将其用于分类器中来确定目标位置.实验结果表明, 该方法在目标受到光照剧烈变化影响的情况下具有很强的适应性, 在目标大小为50 pixel×55 pixel时平均处理帧频可达22 fps.与已有基于压缩感知跟踪算法相比, 该算法在光照变化剧烈的情况下仍具有很好的鲁棒性,而且在目标尺度和纹理发生一定变化的情况下跟踪稳定.

The target tracking algorithm based on compressive sensing can cause the instability or failure in the tracking process when the illumination changes drastically.To deal with such problem , a developed tracking algorithm based on phase congruency was proposed,which is insensitive to the illumination.The phase congruency transformation of the image in the search area is calculated firstly, then the features extracted from the transformed image are used in the classifier to determine the target′s location.Experimental results show that the proposed method has a strong adaptability when the target has a drastic variation in the illumination, and the average frame rate can reach 22 fps when the target size is 50 pixel×55 pixel.Compared with the tracking algorithm based on compressive sensing, the proposed algorithm still has a very good robustness to the drastic variation of the target′s illumination.Besides, to a certain extent, the tracking is also stable to scale and textures change.