Evaluating the effectiveness of height visualizations for improving gestural communication at distributed tabletops

Abstract

In co-located collaboration, people use the space above the table for deictic gestures, and height is an important part of these gestures. However, when collaborators work at distributed tables, we know little about how to convey information about gesture height. A few visualizations have been proposed, but these have not been evaluated in detail. To better understand how remote embodiments can show gesture height, we developed several visualizations and evaluated them in three studies. First, we show that touch visualizations significantly improve people's accuracy in identifying the type and target of a gesture. Second, we show that visualizations of height above the table help to convey gesture qualities such as confidence, emphasis, and specificity. Third, we show that people quickly make use of height visualizations in realistic collaborative tasks, and that height-enhanced embodiments are strongly preferred. Our work illustrates several designs for effective visualization of height, and provides the first comprehensive evidence of the value of height information as a way to improve gestural communication in distributed tabletop groupware.

Visualization of off-surface 3D viewpoint locations in spatial augmented reality

“…Genest et al [5] presented a technique for representing the height of a finger above a collaborative touch screen. However, their concentric circles visualization was not designed to be linearly mapped to the physical height, nor could it be used within the room surrounding the display surface.…”

KinectArms

“…Most trace techniques, however, have only considered mouse movements rather than hand gestures (with Tang et al's work the notable exception [24]), and only show traces when in contact with the surface. Combining historical traces with height visualizations has been discussed [5], but only for telepointer-style embodiments.…”

“…Two exceptions are Fraser et al [4], who showed that representing approaches to a surface can improve distributed interactions, and Genest and Gutwin [5], who showed that abstract representations of height can improve gesture interpretation in distributed settings. Neither solution, however, captured detailed information about the hand and arm: Fraser captured the position of the tip of a stylus and Genest used a single 3D location, tracked with a magnetic-field sensor on the user's pointing finger.…”

“…The height and extents of the table are critical for arm identification, and most systems use an interactive calibration procedure to determine these values [5,9,23]. KinectArms simplifies this step with an automatic table detector.…”

“…Showing the height of a gesture can greatly improve people's ability to interpret the meaning of that gesture [5]. KinectViz provides three kinds of height indicator.…”