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Conference Paper Automated Human Recognition by Gait using Neural Network
Cited 82 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Jang-Hee Yoo, Doo Sung Hwang, Ki-Young Moon, Mark S. Nixon
Issue Date
2008-11
Citation
International Workshops on Image Processing Theory, Tools and Applications (IPTA) 2008, pp.1-6
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/IPTA.2008.4743792
Abstract
We describe a new method for recognizing humans by their gait using back-propagation neural network. Here, the gait motion is described as rhythmic and periodic motion, and a 2D stick figure is extracted from gait silhouette by motion information with topological analysis guided by anatomical knowledge. A sequential set of 2D stick figures is used to represent the gait signature that is primitive data for the feature extraction based on motion parameters. Then, a back-propagation neural network algorithm is used to recognize humans by their gait patterns. In experiments, higher gait recognition performances have been achieved. © 2008 IEEE.
KSP Keywords
Feature extractioN, Gait Recognition, Gait motion, Human Recognition, Motion information, Motion parameters, Periodic motion, Stick figure, back-propagation neural network(BPNN), gait patterns, neural network(NN)