计算机科学 ›› 2021, Vol. 48 ›› Issue (5): 177-183.doi: 10.11896/jsjkx.200300109
陈媛, 惠燕, 胡秀华
CHEN Yuan, HUI Yan, HU Xiu-hua
摘要： 针对跟踪过程中遮挡因素以及目标尺度变化因素导致的目标跟踪漂移问题,文中提出了一种自适应尺度与学习速率调整的背景感知相关滤波跟踪算法。该算法首先通过背景感知相关滤波器获得目标的初步位置信息;其次在背景感知相关滤波器的基础框架下训练尺度相关滤波器,以有效估计目标尺度变化,从而准确调整搜索区域的大小;然后根据响应图波动情况进行遮挡判定,利用平均峰值能量指标与最大响应值判定目标遮挡情况,自适应调整模型学习速率大小;最后,设计相应的模型更新策略,来提高模型性能。在OTB100 Benchmark数据集上进行测试,实验结果表明,该算法与背景感知相关滤波器相比,其成功率提高了6.2%,精度提高了10.1%,因此该算法能有效地处理遮挡、尺度变化等问题,提高了跟踪模型的成功率与准确率,同时具有实时的跟踪速度。
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