ETRI-Knowledge Sharing Plaform



논문 검색
구분 SCI
연도 ~ 키워드


학술지 Automated Markerless Analysis of Human Gait Motion for Recognition and Classification
Cited 102 time in scopus Download 8 time Share share facebook twitter linkedin kakaostory
유장희, Mark S. Nixon
ETRI Journal, v.33 no.2, pp.259-266
한국전자통신연구원 (ETRI)
06MK1500, 고인식 다중생체인식 전용칩셋 기술, 정교일
We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: i) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a knearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines. © 2011 ETRI.
KSP 제안 키워드
Biomechanical parameters, Detection and extraction, Feature extractioN, Further development, Gait motion, Image sequence, Joint angles, Large population, Motion parameters, Recognition and classification, Representation method