This work presents a novel framework for gait recognition augmented with soft biometric information. Geometric gaitanalysis is based on Radon transforms and on gait energy images. User height and stride length information is extracted and utilized in a probabilistic framework for the detection of soft biometric features of substantial discrimination power. Experimental validation illustrates that the proposed approach for integrating soft biometric features in gait recognition advances significantly the identificationand authentication performance.
E. Moustakas, D. Tzovaras and G. Stavropoulos, “Gait recognition using geometric features and soft biometrics”, IEEE Signal Processing Letters, vol. 17, no. 4, pp. 367-370, April 2010.