Domain adaptation for pen trajectory reconstruction from kinematic sensors

Abstract

International audienceHandwriting with connected pen becomes one of the major human-computer easy interaction methods. In comparison with traditional touch screen handwriting systems, the pen-based interaction method has the advantage of producing the online handwriting signal without surface constraints. Indeed, people who write on a paper obtain the corresponding pen trajectory coordinates that represent the online handwriting signal. Furthermore, the feeling of writing on paper is important particularly for the children during the learning of writing. In this work which is part of ANR Franco-German KIHT project with Stabilo, we introduce a domain adaptation-based approach that reconstructs the paper handwriting traces of the digital stylus Digipen of STABILO which is equipped with a wireless trajectory tracking system based on kinematic sensors. We use unsupervised domain adaptation method, to pass from the tablet domain where the ground truth (the online trace of the writing on the tablet) is known, to the paper domain where only the input sensors data are known