SpheriGait：通过球面投影丰富空间表示用于基于LiDAR的步态识别
SpheriGait: Enriching Spatial Representation via Spherical Projection for LiDAR-based Gait Recognition
AI总结：
针对基于LiDAR的步态识别，提出SpheriGait方法，用球面投影替代平面投影增强3D动态特征，并设计DAM-L网络块提取步态线索，在SUSTech1K数据集上达到最先进性能，且可作为通用预处理技术提升其他方法。
摘要：
步态识别是一种快速发展的用于远程识别个体的技术。先前的研究主要采用2D传感器收集步态数据，取得了显著进展；然而，它们不可避免地忽略了3D动态特征对识别的影响。利用LiDAR 3D点云进行步态识别不仅直接捕获3D空间特征，还减少了光照条件的影响，同时确保隐私保护。问题的本质在于如何从点云中有效提取具有判别性的3D动态表示。本文提出了一种名为SpheriGait的方法，用于从点云中提取和增强动态特征，以进行基于LiDAR的步态识别。具体而言，它用球面投影替代传统的点云平面投影方法，以增强对动态特征的感知。此外，提出了一个名为DAM-L的网络块，用于从投影后的点云数据中提取步态线索。我们进行了大量实验，结果表明SpheriGait在SUSTech1K数据集上达到了最先进的性能，并验证了球面投影方法可以作为通用数据预处理技术，以增强其他基于LiDAR的步态识别方法的性能，展现出卓越的灵活性和实用性。
英文摘要：
Gait recognition is a rapidly progressing technique for the remote identification of individuals. Prior research predominantly employing 2D sensors to gather gait data has achieved notable advancements; nonetheless, they have unavoidably neglected the influence of 3D dynamic characteristics on recognition. Gait recognition utilizing LiDAR 3D point clouds not only directly captures 3D spatial features but also diminishes the impact of lighting conditions while ensuring privacy protection.The essence of the problem lies in how to effectively extract discriminative 3D dynamic representation from point clouds.In this paper, we proposes a method named SpheriGait for extracting and enhancing dynamic features from point clouds for Lidar-based gait recognition. Specifically, it substitutes the conventional point cloud plane projection method with spherical projection to augment the perception of dynamic feature.Additionally, a network block named DAM-L is proposed to extract gait cues from the projected point cloud data. We conducted extensive experiments and the results demonstrated the SpheriGait achieved state-of-the-art performance on the SUSTech1K dataset, and verified that the spherical projection method can serve as a universal data preprocessing technique to enhance the performance of other LiDAR-based gait recognition methods, exhibiting exceptional flexibility and practicality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
