现代电子技术2018，Vol.41Issue(1)：71-75,80,6.DOI:10.16652/j.issn.1004-373x.2018.01.016
基于图像识别的中老年人下肢动作运动参数提取方法研究
Research on image recognition based motion parameter extraction method of lower limbs movement of middle-aged and elderly people
摘要
Abstract
The traditional motion parameter extraction method has big extraction error and long time-consumption. There-fore,an image recognition based motion parameter extraction method of lower limbs movement for elderly people is proposed to improve the recognition ability of human motion behavior. On the basis of the speed characteristics of lower limbs movement for the middle-aged and elderly people and the spatiotemporal gradient correlation characteristic of the three-dimensional motion shape,the autocorrelation between the spatial distribution and gradient in the edge gradient direction is solved. The spatiotempo-ral autocorrelation characteristic and video motion feature are combined to satisfy the corresponding data condition of the feature recognition. Because the video image data of human lower limbs movement acts as the typical time series data,the training data is used to construct the complete dictionary according to the local feature of the human skeleton to realize the data encoding. The time domain pyramid matching method is adopted to extract and recognize the characteristic parameter of the lower limbs motion image for the encoded vector. The experimental results show that the proposed method based on image recognition tech-nology can extract the image parameters of the lower limbs movement for the middle-aged and elderly people effectively.关键词
图像识别/下肢动作/自相关性/运动行为识别/时域金字塔匹配法/参数提取Key words
image recognition/lower limbs movement/autocorrelation/motion behavior recognition/time domain pyramid matching method/parameter extraction分类
信息技术与安全科学引用本文复制引用
任彦军,黄丽敏..基于图像识别的中老年人下肢动作运动参数提取方法研究[J].现代电子技术,2018,41(1):71-75,80,6.基金项目
人口老龄化背景下老年人体育健康促进研究(16TYB02)Project Supported by Research on Sports Promotion of the Elderly Under the Background of Population Aging(16TYB02). （16TYB02）
