HLBP与颜色特征自适应融合的粒子滤波目标跟踪改进算法

针对只采用颜色特征的经典粒子滤波目标跟踪算法无法适用相同颜色干扰情况的缺陷,提出一种结合HLBP特征与颜色特征的自适应粒子滤波跟踪算法. 该算法采用Haar型局部二值模式算子(Haar local binary pattern,HLBP)提取的HLBP纹理特征与颜色特征结合,通过自适应权值动态调整颜色特征和纹理特征在追踪过程中的比重,实现颜色纹理特征的自适应融合. 实验表明,该算法改进了相同颜色干扰情况下的追踪效果,并在目标被遮挡的情况下仍能持续稳定地追踪,提高了追踪的准确度和适用性.

Improved Particle Filtering Target Tracking Algorithm forHLBP and Color Feature Adaptive Fusion

In this paper,an adaptive particle filter tracking algorithm combining HLBP feature and color feature is proposed. This algorithm is based on imperfection of the classical particle filter target tracking algorithm:it only uses the color feature to track and does not perform effectively in the same color interference condition. Our algorithm uses the Haar local binary model operator to extract the HLBP texture feature and combine it with the color feature. Through the opposed model,we dynamically adjust adaptive weights of the color characteristics and texture features in the tracking process,which achieve the adaptive fusion between the color feature and texture feature. Experiments show that the tracking result is greatly strengthened under the same color interference with our algorithm. What’s more,in case of occlusions, our algorithm can still track stably and continuously,thus improving the accuracy and applicability of tracking.