基于相关滤波器的图像识别与检测研究

Research on image recognition and detection based on correlation filters

目标识别与检测是计算机视觉的研究热点,其广泛应用于门禁、摄像、无人驾驶等领域。但是遮挡、旋转、背景复杂等问题使目标的识别和检测面临较大挑战。近年来,相关滤波器凭借其在实验中检测速度快、识别率较高、平移不变性等优点备受关注。首先介绍了相关滤波器的基本模型,解释相关滤波器的识别和检测原理。然后详述了多种类型的相关滤波器的发展,包括匹配滤波器、合成判别函数、最优相关输出和其他重要的相关滤波器算法,并通过识别和检测实验证明,相关滤波器算法是有效的。最后基于相关滤波器的发展对其未来的发展给出了几点看法。

Target recognition and detection is a research hotspot in computer vision,widely used in access control,cameras,and unmanned driving.However,the application often encounters problems such as occlusion,rotation,and complex backgrounds,making target recognition and detection even more challenging.In recent years,correlation filters have attracted much attention due to their advantages such as fast detection speed,high recognition accuracy,and translation invariance in experiments.Firstly,the basic model of correlation filters is introduced to explain the principles of correlation filters for recognition and detection.The development of many types of correlation filters,including matched filters,synthetic discriminant functions,optimal correlation outputs,and other important correlation filters is then detailed,and they are effective through recognition and detection experiments.Finally,some points are made about the future development of correlation filters based on their evolution.