TouchPose: Hand Pose Prediction, Depth Estimation, and Touch Classification from Capacitive Images скачать в хорошем качестве

TouchPose: Hand Pose Prediction, Depth Estimation, and Touch Classification from Capacitive Images

TouchPose reconstructs a 3D hand model and a corresponding depth map from the input captured by capacitive touchscreens on today's devices. While current user interfaces typically only detect the coordinates of user input, TouchPose analyzes the mere 2D manifestations of the more complex 3D configuration of the whole hand. TouchPose can power a series of interactive apps and novel interactions on multitouch devices. These applications show TouchPose’s versatile capability to serve as a general-purpose model, operating independent of use-case, and establishing 3D hand pose as an integral part of the input dictionary for application designers and developers. More information: https://siplab.org/projects/TouchPose full publication: Karan Ahuja, Paul Streli, and Christian Holz. TouchPose: Hand Pose Prediction, Depth Estimation, and Touch Classification from Capacitive Images. In Proceedings of ACM UIST 2021. Sensing, Interaction & Perception Lab Department of Computer Science ETH Zürich, Switzerland