Toward Disambiguating Multiple Selections for Frustum-Based Pointing

Abstract

Selection is a fundamental user operation in 3D environments. These environments often simulate or augment the real world, and a part of that simulation is the ability to select objects for observation and manipulation. Many user interfaces for these applications depend on six-degree-of-freedom tracking devices. Such devices have limited accuracy and are susceptible to noise, giving an imprecision that makes object selections difficult and hard to repeat. This difficulty is amplified when the user's viewpoint is also tracked, meaning the user must compensate for noise from both the head tracker and the pointing device when performing object selection. Also, users may experience fatigue when using handheld pointing devices for extended periods, creating error even if the tracking technology were perfect. This paper presents a pointing-based probabilistic selection algorithm that addresses some of the ambiguities associated with tracking and user imprecision. It performs multiple selections by considering a frustum along the user's pointing direction and the hierarchical structure of the database. It assigns probabilities that the user has selected particular objects using a set of low-level 3D intersection-based selection techniques and the relationship of the objects in a hierarchical database, and makes the final selection using one of several weighting schemes. We performed several experiments to evaluate the low-level selection techniques, tested several weighting schemes for the integration algorithm, and we show that the algorithm is effective at disambiguating multiple selections.

The State of the Art of Spatial Interfaces for 3D Visualization

“…A major limitation of ray‐based selections is, of course, the difficulty of selecting small and/or far‐away objects, which is often complicated by hand jitter. Expanding the ray to a cone helps with this [LG94, FHZ96, OBF03, SBB*06, SP04, Ste06], and other primitives may also be used [ZBM94, WHB06, VGC07].…”

Influence of multi-modality on moving target selection in virtual reality

“…Therefore, various methods are proposed to improve user performance and the subjective feelings of target selection. To reduce the limitation of tracking device accuracy, scholars have studied the relationship between gesture pointing motion and cognitive function [24,25] , Schmidt presents a pointing-based probabilistic selection algorithm to reduce tracking uncertainty [26] . Alternatively, the lack of modality information or the difference between the modality information and the real-world cues will reduce user operation performance [27] .…”

Touch & Detach: Ungrouping and observation methods for complex virtual objects using an elastic metaphor

“…Some studies allowed the user to select 3D virtual objects using 3D selection volume. For example, Schmidt et al [16] used a frustum and Ohnishi et al [17] and Haan et al [18] used a cuboid. Another technique enables the user to select multiple objects in more detail.…”