题名 | LidarGait: Benchmarking 3D Gait Recognition with Point Clouds |
作者 | |
DOI | |
发表日期 | 2023
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ISSN | 1063-6919
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ISBN | 979-8-3503-0130-4
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会议录名称 | |
页码 | 1054-1063
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会议日期 | 17-24 June 2023
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会议地点 | Vancouver, BC, Canada
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摘要 | Video-based gait recognition has achieved impressive results in constrained scenarios. However, visual cameras neglect human 3D structure information, which limits the feasibility of gait recognition in the 3D wild world. Instead of extracting gait features from images, this work explores precise 3D gait features from point clouds and proposes a simple yet efficient 3D gait recognition framework, termed LidarGait. Our proposed approach projects sparse point clouds into depth maps to learn the representations with 3D geometry information, which outperforms existing point-wise and camera-based methods by a significant margin. Due to the lack of point cloud datasets, we build the first large-scale LiDAR-based gait recognition dataset, SUSTech1K, collected by a LiDAR sensor and an RGB camera. The dataset contains 25,239 sequences from 1,050 subjects and covers many variations, including visibility, views, occlusions, clothing, carrying, and scenes. Extensive experiments show that (1) 3D structure information serves as a significant feature for gait recognition. (2) LidarGait outperforms existing point-based and silhouette-based methods by a significant margin, while it also offers stable cross-view results. (3) The LiDAR sensor is superior to the RGB camera for gait recognition in the outdoor environment. The source code and dataset have been made available at https://lidargait.github.io. |
关键词 | |
学校署名 | 其他
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相关链接 | [IEEE记录] |
收录类别 | |
WOS记录号 | WOS:001058542601035
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来源库 | IEEE
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全文链接 | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10205455 |
引用统计 |
被引频次[WOS]:32
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成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/559162 |
专题 | 工学院_计算机科学与工程系 |
作者单位 | 1.Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong 2.Department of Computer Science and Engineering, Southern University of Science and Technology 3.Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University |
推荐引用方式 GB/T 7714 |
Chuanfu Shen,Fan Chao,Wei Wu,et al. LidarGait: Benchmarking 3D Gait Recognition with Point Clouds[C],2023:1054-1063.
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条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | 操作 | |
cvpr2023-shen-lidarg(3517KB) | 会议论文 | -- | 限制开放 | CC BY-NC-SA |
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