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This letter presents a novel framework for gait recognition augmented with soft biometric information. Geometric gait analysis 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 identification and authentication performance.