基于多尺度特征融合的跨视角步态识别
DOI:
CSTR:
作者:
作者单位:

1.贵州民族大学数据科学与信息工程学院 贵阳 550025; 2.贵州省模式识别与智能系统重点实验室, 贵州民族大学 贵阳 550025; 3.贵州民族大学人文科技学院 贵阳 550025

作者简介:

通讯作者:

中图分类号:

TP75

基金项目:

国家自然科学基金(62241206)、国家自然科学基金(62162012)、贵州省科技计划项目(黔科合基础-ZK[2022]一般195,黔科合基础-ZK[2023]一般143,黔科合基础-ZK[2022]一般 550,黔科合平台人才-ZCKJ[2021]007)、贵州省高层次创新型人才项目(黔科合平台人才-GCC[2023]027)、贵州省教育厅自然科学研究项目(黔教技[2022]015号)、贵州省教育厅青年科技人才成长项目(黔教技[2023]012号,黔教技[2022]015号,黔教技[2023]061号,黔教技[2023]062号,黔教合KY字[2021]115)、贵州省模式识别与智能系统重点实验室开放课题(GZMUKL[2022]KF01)资助


Cross-view gait recognition based on multi-scale feature fusion
Author:
Affiliation:

1.School of Data Science and Information Engineering, Guizhou Minzu University,Guiyang 550025, China; 2.Key Laboratory of Pattern Recognition and Intelligent System, Guizhou Minzu University,Guiyang 550025, China; 3.College of Humanities & Sciences, Guizhou Minzu University,Guiyang 550025, China

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    在跨视角步态识别中,针对衣着遮挡情况下难以提取具有可辨别性和多样性的步态特征,导致识别准确率下降的问题,提出了一种基于多尺度特征融合网络的跨视角步态识别方法。该方法能够有效利用步态特征间的互补性,获得具有可辨别性和多样性的步态特征,从而解决因衣着遮挡造成可辨别性差以及单一性的问题,进而提升跨视角步态识别的准确性。为验证所提方法的有效性,在公共数据集CASIA-B上进行了验证,实验结果表明所提方法在处理具有遮挡条件下的跨视角步态识别问题的识别性能达到了73.4%,同时在正常和背包两种行走条件下的识别性能分别达到了95.5%和88.0%。此外,我们的方法在处理遮挡条件下的识别性能优于同类典型的步态识别方法。

    Abstract:

    In cross-view gait recognition, it is difficult to extract distinguishable and diverse gait features in the case of clothing occlusion, which leads to the decrease of recognition accuracy. A multi-scale feature fusion network based cross-view gait recognition method is proposed. This method can effectively utilize the complementarity among gait features to obtain gait features with discriminability and diversity, thereby solving the problem of poor discriminability and uniformity caused by clothing occlusion, and thus improving the accuracy of cross-viewing Angle gait recognition. In order to verify the effectiveness of the proposed method, the public data set CASIA-B was used to verify the proposed method. The experimental results show that the proposed method achieves 73.4% recognition performance for the cross-viewing Angle gait recognition problem with occlusion, and 95.5% and 88.0% recognition performance under normal and backpack walking conditions, respectively. In addition, the performance of our method is better than that of other typical gait recognition methods under occluded conditions.

    参考文献
    相似文献
    引证文献
引用本文

邹雪,谭棉,严晓波,王飞,王林.基于多尺度特征融合的跨视角步态识别[J].电子测量技术,2024,47(1):186-192

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2024-04-24
  • 出版日期:
文章二维码
×
《电子测量技术》
财务封账不开票通知