Fall detection using features extracted from skeletal joints and SVM: Preliminary results
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-12405-1.pdf
Reference38 articles.
1. Agahian S, Negin F, Köse C (2019) Improving bag-of-poses with semi-temporal pose descriptors for skeleton-based action recognition. Vis Comput 35 (4):591–607
2. Baskoro AS, Priyono MG (2016) Design of humanoid robot stable walking using inverse kinematics and zero moment point. In: 2016 International electronics symposium (IES). IEEE, pp 335–339
3. Cameron R, Zuo Z, Sexton G, Yang L (2017) A fall detection/recognition system and an empirical study of gradient-based feature extraction approaches. In: UK Workshop on computational intelligence. Springer, pp 276–289
4. Chatzaki C, Pediaditis M, Vavoulas G, Tsiknakis M (2016) Human daily activity and fall recognition using a smartphone’s acceleration sensor. In: International conference on information and communication technologies for ageing well and e-health. Springer, pp 100–118
5. Chen C, Jafari R, Kehtarnavaz N (2015) Utd-mhad: a multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor. In: 2015 IEEE International conference on image processing (ICIP). IEEE, pp 168–172
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Vision-Based Fall Detection Systems Using 3D Skeleton Features for Elderly Security: A Survey;Lecture Notes in Networks and Systems;2024
2. Fall Detection Approaches for Monitoring Elderly HealthCare Using Kinect Technology: A Survey;Applied Sciences;2023-09-15
3. Comparative Analysis Of Deep Learning Models For Human Fall Detection Using Skeleton Features From Video Surveillance System;2023 IEEE Fifth International Conference on Advances in Electronics, Computers and Communications (ICAECC);2023-09-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3