PresentPostures: A Wrist and Body Capture Approach for Augmenting Presentations

Abstract

Capturing and digitizing all nuances during presentations is notoriously difficult. At best, digital slides tend to be combined with audio, while video footage of the presenter’s body language often turns out to be either too sensitive, occluded, or hard to achieve for common lighting conditions. If presentations require capturing what is written on the whiteboard, more expensive setups are usually needed. In this paper, we present an approach that complements the data from a wrist-worn inertial sensor with depth camera footage, to obtain an accurate posture representation of the presenter. A wearable inertial measurement unit complements the depth footage by providing more accurate arm rotations and wrist postures when the depth images are occluded, whereas the depth images provide an accurate full-body posture for indoor environments. In an experiment with 10 volunteers, we show that posture estimates from depth images and inertial sensors complement each other well, resulting in far less occlusions and tracking of the wrist with an accuracy that supports capturing sketches.