Abstract Recent immersive mixed reality (MR) and virtual reality (VR) displays enable users to use their hands to interact with both veridical and virtual environments simultaneously. Therefore, it becomes important to understand the performance of human hand-reaching movement in MR. Studies have shown that different virtual environment visualization modalities can affect point-to-point reaching performance using a stylus, but it is not yet known if these effects translate to direct human-hand interactions in mixed reality. This paper focuses on evaluating human point-to-point motor performance in MR and VR for both finger-pointing and cup-placement tasks. Six performance measures relevant to haptic interface design were measured for both tasks under several different visualization conditions (“MR with indicator,” “MR without indicator,” and “VR”) to determine what factors contribute to hand-reaching performance. A key finding was evidence of a trade-off between reaching “motion confidence” measures (indicated by throughput, number of corrective movements, and peak velocity) and “accuracy” measures (indicated by end-point error and initial movement error). Specifically, we observed that participants tended to be more confident in the “MR without Indicator” condition for finger-pointing tasks. These results contribute critical knowledge to inform the design of VR/MR interfaces based on the application's user performance requirements.
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How Important are Detailed Hand Motions for Communication for a Virtual Character Through the Lens of Charades?
Detailed hand motions play an important role in face-to-face communication to emphasize points, describe objects, clarify concepts, or replace words altogether. While shared virtual reality (VR) spaces are becoming more popular, these spaces do not, in most cases, capture and display accurate hand motions. In this paper, we investigate the consequences of such errors in hand and finger motions on comprehension, character perception, social presence, and user comfort. We conduct three perceptual experiments where participants guess words and movie titles based on motion captured movements. We introduce errors and alterations to the hand movements and apply techniques to synthesize or correct hand motions. We collect data from more than 1000 Amazon Mechanical Turk participants in two large experiments, and conduct a third experiment in VR. As results might differ depending on the virtual character used, we investigate all effects on two virtual characters of different levels of realism. We furthermore investigate the effects of clip length in our experiments. Amongst other results, we show that the absence of finger motion significantly reduces comprehension and negatively affects people’s perception of a virtual character and their social presence. Adding some hand motions, even random ones, does attenuate some of these effects when it comes to the perception of the virtual character or social presence, but it does not necessarily improve comprehension. Slightly inaccurate or erroneous hand motions are sufficient to achieve the same level of comprehension as with accurate hand motions. They might however still affect the viewers’ impression of a character. Finally, jittering hand motions should be avoided as they significantly decrease user comfort.
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- Award ID(s):
- 1652210
- PAR ID:
- 10394435
- Date Published:
- Journal Name:
- ACM Transactions on Graphics
- ISSN:
- 0730-0301
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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