A Method for Animating Children’s Drawings of the Human Figure
Harrison Jesse Smith, Qingyuan Zheng, Yifei Li, Somya Jain, Jessica K. Hodgins
ACM User Interface Software and Technology Symposium (UIST)
In this paper, we present Acustico, a passive acoustic sensing approach that enables tap detection and 2D tap localization on uninstrumented surfaces using a wrist-worn device. Our technique uses a novel application of acoustic time differences of arrival (TDOA) analysis. We adopt a sensor fusion approach by taking both “surface waves” (i.e., vibrations through surface) and “sound waves” (i.e., vibrations through air) into analysis to improve sensing resolution. We carefully design a sensor configuration to meet the constraints of a wristband form factor. We built a wristband prototype with four acoustic sensors, two accelerometers and two microphones. Through a 20- participant study, we evaluated the performance of our proposed sensing technique for tap detection and localization. Results show that our system reliably detects taps with an F1-score of 0.9987 across different environmental noises and yields high localization accuracies with root-mean-square-errors of 7.6mm (X-axis) and 4.6mm (Y-axis) across different surfaces and tapping techniques.
Harrison Jesse Smith, Qingyuan Zheng, Yifei Li, Somya Jain, Jessica K. Hodgins
Yunbo Zhang, Deepak Gopinath, Yuting Ye, Jessica Hodgins, Greg Turk, Jungdam Won
Simran Arora, Patrick Lewis, Angela Fan, Jacob Kahn, Christopher Ré