综合颜色与梯度方向特征的粒子滤波跟踪

针对标准粒子滤波跟踪在复杂环境和光照变化下的缺陷，提出了融合颜色和梯度方向特征的粒子滤波跟踪算法，以克服单一颜色特征跟踪鲁棒性不高的问题。设计了特征融合的粒子重要性评判模型，使得单纯依靠颜色特征不能很好适应环境变化的情况得到了改善。同时通过目标模式自适应更新模型，提高了算法对复杂变化的自适应能力。实验表明，所提算法能比较可靠地实现复杂场景下的目标跟踪。

Color and Gradient Orientation Features Integrated Particle Filter Tracking

Aiming at the visual tracking drawbacks of standard particle filters under the conditions of complex environment and illumination transformation, a new particle filter was proposed based on color and gradient orientation feature to get over the problem of low robustness of the particle filter tracking method through unique feature of color.By designing the model for features fusion, the performance of only color feature was improved when the environment changed. In addition, the proposed target pattern update algorithm improved the adaptability to complex scene diversification. The experiment indicates that the proposed method is effective and robust for the visual tracking under complexbackgrounds.