Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Combined impact of microalbuminuria and obesity on cardiovascular outcomes in hospitalized heart failure patients: a cohort study.

BMC cardiovascular disorders·2026
Same author

Screening of SIGLEC1 based on transcriptomics and investigation of its function and mechanism in regulating mycobacterium tuberculosis-induced injury and polarization in THP-1 macrophages.

Archives of microbiology·2026
Same author

Rhein antagonizes glucocorticoid receptor signaling to activate SIRT1-dependent thermogenesis in brown adipose tissue and ameliorate obesity.

Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
Same author

Lactate related metabolic reprogramming increases global protein lactylation and remodels tumor immune microenvironment of hepatocellular carcinoma.

Pakistan journal of pharmaceutical sciences·2026
Same author

Seven-day Venetoclax Combined With Dose-adjusted Intensive Chemotherapy as Induction Treatment in Newly Diagnosed Acute Myeloid Leukemia.

Clinical lymphoma, myeloma & leukemia·2026
Same author

Incremental Prognostic Value of Heart-Type Fatty Acid Binding Protein in Patients With Light Chain Cardiac Amyloidosis: A Prospective Cohort Study.

Clinical and translational science·2026

相关实验视频

Updated: Jul 6, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

基于时间3D点云深度学习的水面和水下人类姿势识别.

Haijian Wang1, Zhenyu Wu1, Xuemei Zhao2

  • 1School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China.

Scientific reports
|January 3, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了光检测和距离测定 (LiDAR) 用于同时在水面和水下识别人类姿势. 这种新的方法实现了高精度,提高了安全和监控能力.

更多相关视频

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

487
Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.8K

相关实验视频

Last Updated: Jul 6, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

487
Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.8K

科学领域:

  • 机器人和计算机视觉 机器人和计算机视觉
  • 遥感技术 遥感技术
  • 人与计算机的交互

背景情况:

  • 由于可见光波长限制,空中光学摄像机在同时成像水面和水下环境方面面临限制.
  • 准确的人体姿势识别对于安全和监视至关重要,特别是在遇险或溺水的情况下检测个人.

研究的目的:

  • 提出和验证一种使用光探测和距离测量 (LiDAR) 的新方法,用于同时在水面和水下识别人类姿势.
  • 开发一种能够从不规则的时间点云数据识别人类姿势的神经网络.

主要方法:

  • 用于水面和水下人类姿势识别的时间点云数据集的构建.
  • 应用半径异常值去除 (ROR) 和统计异常值去除 (SOR) 来减少数据噪声.
  • 使用PointNet++优化识别准确度,使用各种二次采样方法和样本大小.

主要成果:

  • 拟议的方法成功实现了在水面和水下同时检测和识别人类的姿势.
  • 在优化采样技术和尺寸后,最高的识别精度达到97.5012%.
  • 证明了设计用于姿势识别中不规则数据的神经网络的有效性.

结论:

  • 光探测和距离测定 (LiDAR) 为克服光学摄像机在双环境人类姿势识别中的局限性提供了一个可行的解决方案.
  • 开发的神经网络方法,结合数据预处理和优化,在复杂的场景中显著提高了人类姿势检测的准确性.
  • 这项研究为水和地表环境中的先进安全和监控系统提供了坚实的基础.