Notice of RetractionGait recognition using the temporal information of leg angles

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Gait recognition is of increasing interest recently. A gait recognition method using the temporal information of leg angles is proposed, based on the fact that changes of leg angles can reflect main trait of a man´s moving. First the pendulum model is referred to for extracting leg parts, and least-square method is used for boundary fitting, to obtain the temporal information of angle about thigh and shin. Then, the acquired temporal information is expanded in Fourier series form, in consideration of walking activity´s periodic property. Genetic algorithm is subsequently adopted to search for the harmonic coefficients, which are normalized to produce the gait signature. Finally, NN and ENN classifiers are both applied to do the sorting task. Experimental results on CMU database show that the proposed method has high recognition rates. Furthermore, self-occlusion problem, which may often be encountered in gait recognition, is well handled by this method.