Analysis of Proximity-Based Multimodal Feedback for 3D Selection in Immersive Virtual Environments

Interaction tasks in virtual reality (VR) such as three-dimensional (3D) selection or manipulation of objects often suffer from reduced performance due to missing or different feedback provided by VR systems than during corresponding realworld interactions. Vibrotactile and auditory feedback have be...

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Vydáno v:2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) s. 327 - 334
Hlavní autoři: Ariza, Oscar, Bruder, Gerd, Katzakis, Nicholas, Steinicke, Frank
Médium: Konferenční příspěvek
Jazyk:angličtina
japonština
Vydáno: IEEE 01.03.2018
Témata:
Evaluation
Feeds
H.5.2 [Information Interfaces and Presentation]: User Interfaces-Input Devices and Strategies
Haptic interfaces
Performance evaluation
Task analysis
Three-dimensional displays
Two dimensional displays
Visualization
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Shrnutí:Interaction tasks in virtual reality (VR) such as three-dimensional (3D) selection or manipulation of objects often suffer from reduced performance due to missing or different feedback provided by VR systems than during corresponding realworld interactions. Vibrotactile and auditory feedback have been suggested as additional perceptual cues complementing the visual channel to improve interaction in VR. However, it has rarely been shown that multimodal feedback improves performance or reduces errors during 3D object selection. Only little research has been conducted in the area of proximity-based multimodal feedback, in which stimulus intensities depend on spatiotemporal relations between input device and the virtual target object. In this paper, we analyzed the effects of unimodal and bimodal feedback provided through the visual, auditory and tactile modalities, while users perform 3D object selections in VEs, by comparing both binary and continuous proximity-based feedback. We conducted a Fitts' Law experiment and evaluated the different feedback approaches. The results show that the feedback types affect ballistic and correction phases of the selection movement, and significantly influence the user performance.
DOI:10.1109/VR.2018.8446317