【摘要】：提出了一種基于蝙蝠算法的目標跟蹤新方法.首先描述了基于蝙蝠算法的目標跟蹤流程,在此基礎上研究了蝙蝠算法的迭代終止條件、蝙蝠種群數、脈沖頻率因子和脈沖音強衰減因子對跟蹤性能的影響,并通過實驗確定了以上參數,最后與粒子濾波、均值漂移和粒子群優(yōu)化3種跟蹤算法進行了比較.實驗結果表明,基于蝙蝠算法的視頻目標跟蹤方法的跟蹤效果優(yōu)于其他3種算法.
[Abstract]:A new target tracking method based on bat algorithm is proposed. Firstly, the object tracking process based on bat algorithm is described. Based on this, the iterative termination conditions of bat algorithm, the effects of bat population number, pulse frequency factor and pulse tone attenuation factor on tracking performance are studied. The above parameters are determined by experiments, and compared with three tracking algorithms: particle filter, mean shift and particle swarm optimization. The experimental results show that the video target tracking method based on bat algorithm is better than the other three algorithms.
【作者單位】： 山東理工大學電氣與電子工程學院;西南石油大學計算機科學學院;
【基金】：國家自然科學基金項目(61601266) 山東理工大學青年教師支持計劃項目 山東省自然科學基金聯合專項項目(ZR2015FL034)
【分類號】：TP391.41
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本文編號：2405567