基于随机蕨丛的长期目标跟踪算法

为了从根本上解决运动目标遮挡、环境光照变化、目标外观变化、目标运动速度过快等复杂情况下的目标跟踪问题，采用了将目标检测与标准的目标跟踪算法相结合的目标跟踪框架，提出了基于双向一致性误差评估的标准跟踪算法，提高了跟踪点的可靠性；采用随机蕨丛算法作为目标检测的主体，很好地解决了目标遮挡、消失等情况导致跟踪失败后无法重新初始化的问题.通过实验验证了所提出的目标跟踪算法能实现目标的长期跟踪，且具有很强的适用性.

Long Term Object Tracking Algorithm Based on Random Ferns

In order to realize the object tracking in complex situation such as occlusions, partial and full changing illuminations, appearance change or fast motion, a novel object tracking framework was proposed by adopting the method that combined standard object tracking with object detection. The tracking algorithm based on the error of the evaluation standard two-way consistency was put forward to improve the reliability of the tracking point. The target detection algorithm based on random fern plexus was able to initialize objective to again track object, when the object was sheltered and disappear, failure to track. The proposed object tracking algorithm was proved to be able to achieve the goal of long-term tracking and be very robust.