Title :
Extracting human gait signatures by body segment properties
Author :
Yoo, Jang-Hee ; Nixon, Mark S. ; Harris, Chris J.
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Abstract :
We describe a new method for extracting human gait signatures by topological analysis, using properties of body segments. The gait signature is extracted in three stages: extraction of the body contour by a thresholding and morphological filter; extraction of the leg angles based on regression analysis of contour data; finding the body points guided by known anatomical knowledge. A 2D stick figure is used to represent the human body model and trajectory-based kinematic features are extracted from the image sequences for describing and analyzing the gait motion. Also, the inherent periodicity in gait motion is analyzed by delay coordinates and a phase-space portrait. The utility of the proposed method is demonstrated in experiments, with comparison to medical data
Keywords :
backpropagation; feature extraction; gait analysis; image sequences; neural nets; physiological models; statistical analysis; topology; 2D stick figure; anatomical knowledge; backpropagation neural network algorithm; body contour; body points; body segment properties; gait analysis; human body model; human gait signatures; image sequences; kinematic feature extraction; leg angles; morphological filter; regression analysis; thresholding filter; topological analysis; trajectory-based feature extraction; Biological system modeling; Data mining; Feature extraction; Filters; Humans; Image motion analysis; Kinematics; Leg; Motion analysis; Regression analysis;
Conference_Titel :
Image Analysis and Interpretation, 2002. Proceedings. Fifth IEEE Southwest Symposium on
Conference_Location :
Sante Fe, NM
Print_ISBN :
0-7695-1537-1
DOI :
10.1109/IAI.2002.999885
