多种信息融合的实时在线多目标跟踪

摘要

The multiple object tracking ( MOT) algorithm will fail when its target is occluded or in fast motion,furthermore,it cannot recover from drifting. To solve these problems, firstly, we employ integrated information to enhance the representation of objects, which includes the target's appearance, shape and motion information. By means of the integrated information,we can accurately calculate the similarity,which is as similar as possible between the same targets and as different as possible between the different targets.Secondly,we propose a novel real-time single object tracker based on the combination of the discriminative correlation filters ( DCF) and the Kalman filters,which is robust to occlusion and fast motion.Extensive experiments have been done,and results show that the proposed MOT algorithm can accurately track the target in case of occlusion or fast motion in real time.%多目标跟踪算法在目标发生遮挡、目标快速运动时容易跟踪失败,而且无法从失败中恢复跟踪.针对该问题,首先利用目标的外观信息、运动信息和形状信息多种信息融合的目标特征表示,准确地计算目标间的相似性,使同一目标之间相似性距离尽量小,不同目标间的相似性距离尽量大;其次,基于判别能力强大的相关滤波器和卡尔曼预估器结合的单目标跟踪器可以在目标遮挡、快速运动中准确地跟踪目标.实验结果表明,多目标跟踪算法能够实时准确地跟踪被遮挡的目标和快速运动的目标.