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Detail
Journal Article
Automated Markerless Analysis of Human Gait Motion for Recognition and Classification
- Authors
- Jang-Hee Yoo, Mark S. Nixon
- Issue Date
- 2011-04
- Citation
- ETRI Journal, v.33, no.2, pp.259-266
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- 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 Keywords
- Biomechanical parameters, Detection and extraction, Feature extractioN, Further development, Gait motion, Image sequences, K-Nearest Neighbor(KNN), Large population, Motion parameters, Recognition and classification, Representation method