Gait kinematics as a biometric for identification

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Abstract Summary
Gait, considered by many, is distinguishable between individuals, making gait a viable security measure. The long-term goal of this research is to identify specific individuals wearing clothing with a high level of accuracy using a convolutional neural network (CNN). In this study, a supervised binary classification algorithm was developed and trained to identify subjects based on motion capture data.
Submission ID :
UCB703
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