Leveraging finger identification to integrate multi-touch command selection and parameter manipulation

Abstract

International audienceIdentifying which fingers are touching a multi-touch surface provides a very large input space. We describe FingerCuts, an interaction technique inspired by desktop keyboard shortcuts to exploit this potential. FingerCuts enables integrated command selection and parameter manipulation, it uses feed-forward and feedback to increase discoverability, it is backward compatible with current touch input techniques, and it is adaptable for different touch device form factors. We implemented three variations of FingerCuts, each tailored to a different device form factor: tabletop, tablet, and smartphone. Qualitative and quantitative studies conducted on the tabletop suggests that with some practice, FingerCuts is expressive, easy-to-use, and increases a sense of continuous interaction flow and that interaction with FingerCuts is as fast, or faster than using a graphical user interface. A theoretical analysis of FingerCuts using the Fingerstroke-Level Model (FLM) matches our quantitative study results, justifying our use of FLM to analyse and validate the performance for the other device form factors

Quantifying Differences among Ten Fingers in Force Control Capabilities by a Modified Meyer Model

“…Results from Antal et al [46] showed that these additional features enhance the accuracy of both processes. Hereby, these studies suggested a heuristic supporting the pattern analysis and recognition of tapping fingers by checking responding finger of each typing, similar to fingerprint identification [47,48]. Keystroke dynamics of finger force control for user authentication has become an active research area due to its low cost and ease of integration with existing security systems.…”

Reducing error aversion to support novice-to-expert transitions with FastTap

“…For example, some systems show "gesture guides" when a user begins a gesture, to indicate what legal gestures can be completed [3,9]. Similarly, Arpège and FingerCuts show completion possibilities for multitouch chords [13,15]. On the desktop, ExposeHK [22] exposes keyboard shortcuts beside interface buttons when a modier key is pressed.…”

WhichFingers

“…Other prototypes developed in the literature are mainly based on contacts geometry [1,5,9,31,18,29], RGB and depth cameras [4,11,13,17,24,30,33], and fingerprints [27,16].…”

“…RGB cameras have been used to recognize specific hand postures involving different fingers [17,21]. Depth cameras can help to segment the hand from the background [24] but as soon as the hand can interact more freely, fingers need to be equipped with color rings to improve the robustness of detection [11,13,30]. Leap Motion has been investigated but it requires users to first open the hand such that the algorithm identifies the 5 fingers, and then fold the fingers such that the finger selected for interaction is the furthest away from the others [4].…”

“…Other applications explore the use of common two-finger gestures (e.g. 2-fingers swipes) [2,13]. However, when it comes to chords with more than two fingers, they use sequential construction of chord (e.g.…”