PrintShear

Abstract

Most touch-based input devices, such as touchscreens and touchpads, capture low-resolution capacitive images when a finger touches the device's surface. These devices only output the two-dimensional (2D) positions of contacting points, which are insufficient for complex control tasks, such as the manipulation of 3D objects. To expand the modalities of touch inputs, researchers have proposed a variety of techniques, including finger poses, chording gestures, touch pressure, etc. With the rapid development of fingerprint sensing technology, especially under-screen fingerprint sensors, it has become possible to generate input commands to control multiple degrees of freedom (DOF) at a time using fingerprint images. In this paper, we propose PrintShear, a shear input technique based on fingerprint deformation. Lateral, longitudinal and rotational deformations are extracted from fingerprint images and mapped to 3DOF control commands. Further DOF expansion can be achieved through recognition of the contact region of the touching finger. We conducted a 12-person user study to evaluate the performance of PrintShear on 3D docking tasks. Comparisons with other input methods demonstrated the superiority of our approach. Specifically, a 19.79% reduction in completion time was achieved compared with conventional touch input in a full 6DOF 3D object manipulation task.