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Silhouettes versus skeletons in gesture-based authentication with Kinect

Since its release, the Kinect has been successfully used in gesture recognition. Recent work has extended Kinect's use towards biometric user authentication based on face, speech, gait, and gestures. Our work expands on the last of these modalities - gestures, which have yielded promising authentication results in prior work. This paper aims to gain insight into how authentication methods that are based on silhouette features compare against those that are based on skeletal features in terms of trade-offs between authentication performance and robustness against some real-world degradations. On a dataset of 40 users that contains two types of degradations namely, user-memory and personal-effects (heavy coats, bags, etc.), we found that for user-defined gestures, skeletal features outperform silhouettes on average by 4.89% in terms of the Equal Error Rate (EER).