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Individual recognition using gait energy image

机译:使用步态能量图像进行个人识别

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摘要

In this paper, we propose a new spatio-temporal gait representation, called gait energy image (GEI), to characterize human walking properties for individual recognition by gait. To address the problem of the lack of training templates, we also propose a novel approach for human recognition by combining statistical gait features from real and synthetic templates. We directly compute the real templates from training silhouette sequences, while we generate the synthetic templates from training sequences by simulating silhouette distortion. We use a statistical approach for learning effective features from real and synthetic templates. We compare the proposed GEI-based gait recognition approach with other gait recognition approaches on USF HumanID Database. Experimental results show that the proposed GEI is an effective and efficient gait representation for individual recognition, and the proposed approach achieves highly competitive performance with respect to the published gait recognition approaches.
机译:在本文中,我们提出了一种新的时空步态表示方法,称为步态能量图像(GEI),以表征人的步行特性,以通过步态进行个体识别。为了解决缺少训练模板的问题,我们还提出了一种通过结合来自真实模板和合成模板的统计步态特征来进行人类识别的新方法。我们直接从训练轮廓序列中计算出真实模板,而通过模拟轮廓失真从训练序列中生成合成模板。我们使用统计方法从实际和合成模板中学习有效功能。我们将提出的基于GEI的步态识别方法与USF HumanID数据库上的其他步态识别方法进行了比较。实验结果表明,提出的GEI是一种有效且高效的步态表示方法,可用于个人识别,并且相对于已发表的步态识别方法,该方法具有很高的竞争性能。

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