计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 164-169.doi: 10.11896/jsjkx.190500013
裴嘉震, 徐曾春, 胡平
PEI Jia-zhen, XU Zeng-chun, HU Ping
摘要: 行人再识别是视频监控中一项极具挑战性的任务。图像中的遮挡、光照、姿态、视角等因素,会对行人再识别的准确率造成极大影响。为了提高行人再识别的准确率,提出一种融合视点机制与姿态估计的行人再识别方法。首先,采用姿态估计算法Openpose定位行人关节点;然后,对行人图像进行视图判别以获得视点信息,并根据视点信息与行人关节点位置进行局部区域推荐,生成行人局部图像;接着,将全局图像与局部图像同时输入CNN提取特征;最后,采用特征融合网络将全局与局部的特征融合,以获取更具鲁棒性的特征表示。实验结果表明:提出的方法具有更高的行人再识别准确率,其在CHUK03数据集上的rank1达到了71.3%,在Market1501和DukeMTMC-reID数据集上的mAP分别达到了63.2%与60.5%。因此,所提方法能够很好地应对行人姿态变化和视角变化等问题。
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