Abstract:The Virtual Table presents stereoscopic graphics to a user in a workbench-like setting. This paper reports on a user interface and new interaction techniques for the Virtual Table based on transparent props-a tracked hand-held pen and a pad. These props, but in particular the pad, are augmented with 3D graphics from the Virtual Table's display. This configuration creates a very powerful and flexible interface for two-handed interaction that can be applied to other back-projected stereographic displays as well:… Show more
“…As we noted in our design-space exploration in chapter 2, one strategy for mitigating the drawbacks of intangible interfaces is the provision of palette-like objects for use in virtual settings [82,183,199]. Another influential technique, introduced by Billinghurst et al [24], uses fiducial makers to act as both tracking support and proxy objects for virtual counterparts.…”
“…As we noted in our design-space exploration in chapter 2, one strategy for mitigating the drawbacks of intangible interfaces is the provision of palette-like objects for use in virtual settings [82,183,199]. Another influential technique, introduced by Billinghurst et al [24], uses fiducial makers to act as both tracking support and proxy objects for virtual counterparts.…”
“…For example, Schmalstieg et al [69] suggested to use transparent props, yet these are static and would not work well with 3D data space manipulations and time-dependent data. Hachet et al [31] separated the touch surface from the stereoscopic display in their Toucheo system, but thus significantly restricted the space in which people can interact.…”
Section: D Stereoscopic Viewing Of 3d Data Visualizationsmentioning
6 . The text of this author version is virtually identical to the published one, albeit uses better typography and more hyperlinks (e. g., from the figures to online videos of the described interaction technique(s)). Notice also that many of the images contained in the publisher's online version are of lower quality than those contained in this author-prepared version.Abstract The chapter surveys the different approaches investigated to interact with scientific visualizations on large surfaces such as tables and walls. The chapter particularly does not focus on VR-based interaction or tangible input but on those interaction techniques where the input is provided on the surface itself or where it is focused on the surface. In particular, tactile interaction techniques are covered and the challenges of gestural input as well as of combining touch input with stereoscopic rendering are discussed. Where possible, connections to collaborative interaction scenarios are pointed out, even though most publications to date focus on single-user interaction.
“…This gesture is particularly well-suited to touch-screen based interactions. For instance, Schmalstieg et al used the circling metaphor to select objects in a virtual world [28]. As for the straight strokes, heuristics are here used to recognize circular sketches, based on the shape of the stroke and the distance between the first and the last point of the sketch.…”
integrated system for teaching new visually grounded words to a robot for non-expert users using a mobile device. Abstract-In this paper, we present a system allowing nonexpert users to teach new words to their robot. In opposition to most of existing works in this area which focus on the associated visual perception and machine learning challenges, we choose to focus on the HRI challenges with the aim to show that it may improve the learning quality. We argue that by using mediator objects and in particular a handheld device, we can develop a human-robot interface which is not only intuitive and entertaining but will also "help" the user to provide "good" learning examples to the robot and thus will improve the efficiency of the whole learning system. The perceptual and machine learning parts of this system rely on an incremental version of visual bag-of-words. We also propose a system called ASMAT that makes it possible for the robot to incrementally build a model of a novel unknown object by simultaneously modelling and tracking it. We report experiments demonstrating the fast acquisition of robust object models using this approach.
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