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中文摘要：
对于基准背景已知的固定场景,提出估测人数的四步框架,相比2010年D.Conte等的结果显著提高远距离人群的估测精度.精度提高的主要原因在于＂非最大抑制聚类＂,这种基于密度的聚类方法对不同拍摄距离的人群采取不同的聚类标准,避免类过大造成的后续问题.PETS2010数据库的实验表明,远距离高密度人群因被分为多类,估测精度明显提高.
英文摘要：
Based on the background image of a fixed scene,a four-step approach to count predestrains in video sequences is presented,and the estimation result of long-range crowds is improved compared with D.Conte＇s solution in 2010 EURASIP Journal.Our primary contribution lies in non-maxima suppression clustering.The proposed density-based clustering approach applies different clustering standards to crowds at different distances from camera,hence it avoids overlarge clusters and ensuing problems.Experiments on PETS 2010 database show estimation result of long-range crowds is improved significantly,as an implicit result of smaller clusters from Non-maxima Suppression Clustering.
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