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Moving Target Detection and Tracking for Smartphone Automatic Focusing 被引量:1

Moving Target Detection and Tracking for Smartphone Automatic Focusing
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摘要 In this paper,a non-contact auto-focusing method is proposed for the essential function of auto-focusing in mobile devices.Firstly,we introduce an effective target detection method combining the 3-frame difference algorithm and Gauss mixture model,which is robust for complex and changing background.Secondly,a stable tracking method is proposed using the local binary patter feature and camshift tracker.Auto-focusing is achieved by using the coordinate obtained during the detection and tracking procedure.Experiments show that the proposed method can deal with complex and changing background.When there exist multiple moving objects,the proposed method also has good detection and tracking performance.The proposed method implements high efficiency,which means it can be easily used in real mobile device systems. In this paper,a non-contact auto-focusing method is proposed for the essential function of auto-focusing in mobile devices.Firstly,we introduce an effective target detection method combining the 3-frame difference algorithm and Gauss mixture model,which is robust for complex and changing background.Secondly,a stable tracking method is proposed using the local binary patter feature and camshift tracker.Auto-focusing is achieved by using the coordinate obtained during the detection and tracking procedure.Experiments show that the proposed method can deal with complex and changing background.When there exist multiple moving objects,the proposed method also has good detection and tracking performance.The proposed method implements high efficiency,which means it can be easily used in real mobile device systems.
出处 《ZTE Communications》 2017年第1期55-60,共6页 中兴通讯技术(英文版)
基金 supported by ZTE Industry-Academia-Research Cooperation Funds
关键词 moving target detection frame.difference METHOD background modeling METHOD CAMSHIFT TRACKING MEANSHIFT TRACKING autofocusing moving target detection frame-difference method background modeling method camshift tracking meanshift tracking auto-focusing
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