Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion
Pattern Recognition Letters
Computing and evaluating view-normalized body part trajectories
Image and Vision Computing
A study on gait-based gender classification
IEEE Transactions on Image Processing
Wavelet analysis of cyclic human gait for recognition
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Gait recognition based on time-frequency analysis
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Gait recognition without subject cooperation
Pattern Recognition Letters
Vs-star: A visual interpretation system for visual surveillance
Pattern Recognition Letters
Gait recognition based on fusion of multi-view gait sequences
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Gait recognition using wavelet descriptors and independent component analysis
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Modelling the effect of view angle variation on appearance-based gait recognition
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Reducing the effect of noise on human contour in gait recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Performance analysis of matrix gait recognition under linear interpolation framework
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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In this paper, we analyze the spatio-temporal human characteristic of moving silhouettes in frequency domain, and find key Fourier descriptors have better discriminatory capability for recognition than other Fourier descriptors. A large number of experimental results and analysis show that the proposed algorithm based on the key Fourier descriptors can not only reduce the gait data dimensionality greatly, but also lighten the computation cost, with a satisfactory CCR. Besides that, classification performance can be further improved using feature fusion.