Design and evaluation of 3D selection techniques based on progressive refinement

Bacim, Felipe; Kopper, Regis; Bowman, Doug A.

doi:10.1016/j.ijhcs.2013.03.003

Cited by 49 publications

(32 citation statements)

References 30 publications

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“…While most 3D selection techniques rely on simple selection shapes, some make use of progressive refinement strategies to improve the precision of the final 3D volume (e. g., [BKB13, EDF08, KBB11, YEII12, YEII16]). We use a similar approach based on Boolean operations, either adding to (OR), intersecting with (AND), or subtracting from the previous selection (AND NOT).…”

Section: Tangible Selection Brushmentioning

confidence: 99%

Hybrid Touch/Tangible Spatial 3D Data Selection

Besançon

Sereno

et al. 2019

Computer Graphics Forum

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We discuss spatial selection techniques for three‐dimensional datasets. Such 3D spatial selection is fundamental to exploratory data analysis. While 2D selection is efficient for datasets with explicit shapes and structures, it is less efficient for data without such properties. We first propose a new taxonomy of 3D selection techniques, focusing on the amount of control the user has to define the selection volume. We then describe the 3D spatial selection technique Tangible Brush, which gives manual control over the final selection volume. It combines 2D touch with 6‐DOF 3D tangible input to allow users to perform 3D selections in volumetric data. We use touch input to draw a 2D lasso, extruding it to a 3D selection volume based on the motion of a tangible, spatially‐aware tablet. We describe our approach and present its quantitative and qualitative comparison to state‐of‐the‐art structure‐dependent selection. Our results show that, in addition to being dataset‐independent, Tangible Brush is more accurate than existing dataset‐dependent techniques, thus providing a trade‐off between precision and effort.

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Section: Tangible Selection Brushmentioning

confidence: 99%

Hybrid Touch/Tangible Spatial 3D Data Selection

Besançon

Sereno

et al. 2019

Computer Graphics Forum

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“…Area cursors are especially appropriate for individuals with motor control impairments or difficulties [26,5]. Similar ideas have also been extended into 3D to provide selection with progressive refinement in 3D scenes [1]. All area and space cursors necessitate disambiguation when there are multiple targets and no clear winner.…”

Section: Area Cursorsmentioning

confidence: 99%

Hobs

Zhang

Chen

Tuna

et al. 2014

Proceedings of the 2nd ACM Symposium on Spatial User Interaction

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Figure 1. Left: Our head orientation-based selection techniques use an IR emitter -multiple targets may fall within its illumination area. Center: We offer two list-based refinement techniques -Naive IR uses alphabetical ordering; Intensity IR orders targets by IR intensity. Right: Using Head-motion Refinement technique, users can refine their selection through head orientation refinement in a quasi-mode when they hold the touchpad. ABSTRACTEmerging head-worn computing devices can enable interactions with smart objects in physical spaces. We present the iterative design and evaluation of HOBS -a Head OrientationBased Selection technique for interacting with these devices at a distance. We augment a commercial wearable device, Google Glass, with an infrared (IR) emitter to select targets equipped with IR receivers. Our first design shows that a naive IR implementation can outperform list selection, but has poor performance when refinement between multiple targets is needed. A second design uses IR intensity measurement at targets to improve refinement. To address the lack of natural mapping of on-screen target lists to spatial target location, our third design infers a spatial data structure of the targets enabling a natural head-motion based disambiguation. Finally, we demonstrate a universal remote control application using HOBS and report qualitative user impressions.

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“…Zoom: Bacim et al [6] propose two techniques for progressive refinement based on zoom, discrete zoom and continuous zoom. In the discrete zoom, the user defines a quadrant of the screen they want to see in more detail, the frustum changes so that the specific quadrant covers all the field of view (FOV).…”

Section: Related Workmentioning

confidence: 99%

“…It aims to avoid the attention and precision usually required by traditional selection techniques, so-called immediate selection techniques [5,6]. However, there is an inevitable tradeoff between immediate and progressive refinement selection techniques.…”

Section: Introductionmentioning

confidence: 99%