Extending the eSIGN Editor to Specify More Dynamic Signing

In this paper, we present the time alignment process to match the dynamics of human signing with the scripted sign (avatar). We replace the manual editing process with a Kinect-based approach. While the current state of the art in sign language recognition does not allow reliable recognition of fluent signing, we will show that it is possible to extract the dynamics of the user’s sign performance and apply it to a pre-existing sign script featuring the exact same signs. The user manually defines a sign script and then signs it into the Kinect for the system to get the dynamics as performed by the user. A dataset of selected signs have been created for the experimentation purpose with the proposed approach and our approach’s performance analysis has been described in detail in this paper.