中文摘要：

提出了一种多特征融合粒子滤波跟踪算法，并利用 GPU （Graphic Processing Unit）技术对算法进行了并行优化。针对单一特征描述目标模型的缺陷，此算法采用了具有互补性的灰度与梯度直方图特征建立目标模型，从而提高粒子滤波算法跟踪的稳定性和精度。同时，针对粒子滤波计算量大的缺点，此算法对粒子滤波进行了基于GPU 的并行优化设计和实现，从而提升跟踪算法的计算速度。可以满足算法的实时性应用。

英文摘要：

A parallel particle filter object tracking algorithm is given out,which is based on multiple feature fusion with the help of GPU （Graphic Processing Unit）technology.Due to the limitation of the model representation based on single visual feature,two complementary visual features,which are gray histogram and gradient histogram,are used in the algorithm to improve the tracking stability and accuracy.Moreover,to handle the large amount computation cost of the particle filter,a GPU parallel optimized scheme is designed to improve the algorithm speed. and can meet the real-time application requirement.