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학술대회 Automated Human Recognition by Gait using Neural Network
Cited 67 time in scopus Download 1 time Share share facebook twitter linkedin kakaostory
저자
유장희, 황두성, 문기영, Mark S. Nixon
발행일
200811
출처
International Workshops on Image Processing Theory, Tools and Applications (IPTA) 2008, pp.1-6
DOI
https://dx.doi.org/10.1109/IPTA.2008.4743792
협약과제
08MS2800, 프라이버시 보호형 바이오인식 시스템 개발, 문기영
초록
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.
키워드
Gait, Gait biometrics, Human motion
KSP 제안 키워드
Back Propagation(BP), Feature extractioN, Gait motion, Gait recognition, Human Recognition, Human motion, Motion information, Motion parameters, Neural network algorithm, Periodic motion, Stick figure