近年来，非刚体目标跟踪技术作为视频目标跟踪中的一个难点受到了广泛关注。为了精确跟踪非刚体目标，克服跟踪过程中目标形状变化和遮挡带来的困难，提出一种基于活动基模型的非刚体目标跟踪算法。首先采用共享草图算法从目标训练样本集中学习得到目标的活动基模型，然后把活动基模型嵌入粒子滤波观测模型中。在对金鱼与企鹅序列跟踪的实验结果表明,与现有算法相比，该算法在非刚体目标形状变化以及存在遮挡的情况下，具有更好的跟踪性能。

Recently, as a difficult problem in video object tracking non-rigid object tracking has received much more attention. To track non-rigid objects exactly and solve the problem caused by shape deformation, this paper proposes a non-rigid object tracking algorithm based on active basis model. Firstly, the object active basis model was learned from the training set using a shared sketch algorithm. Secondly, the learned active model is embedded in a particle filter. The experimental results show that our algorithm is more robust than other methods when non-rigid object has shape deformation and occlusion happens.