PRECIOUS! Out-of-reach selection using iterative refinement in VR

Mendes, Daniel; Medeiros, Daniel; Cordeiro, Eduardo; Sousa, Maurício; Ferreira, Alfredo; Jorge, Joaquim

doi:10.1109/3dui.2017.7893359

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…Moreover LenSelect has only been compared to ray-based selection techniques. In especially cluttered environments other approaches might prove more fruitful, like Starfish (Wonner et al, 2012) or teleportation (Mendes et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…The Go-Go technique (Bowman and Hodges, 1997a), and its extension Stretch Go-Go (Bowman and Hodges, 1997a), try to bring objects closer to the user by non-linearly scaling the radial distance of the user's virtual hand from the user's body, while still maintaining the isomorphic scaling of the user's hand in the tangential directions. PRECIOUS works the other way round, teleporting the user close to the target for target acquisition, then sending them back to their initial location (Mendes et al, 2017).…”

Section: Related Workmentioning

confidence: 99%

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LenSelect: Object Selection in Virtual Environments by Dynamic Object Scaling

Weller

Wegele

Schröder

et al. 2021

Front. Virtual Real.

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We present a novel selection technique for VR called LenSelect. The main idea is to decrease the Index of Difficulty (ID) according to Fitts’ Law by dynamically increasing the size of the potentially selectable objects. This facilitates the selection process especially in cases of small, distant or partly occluded objects, but also for moving targets. In order to evaluate our method, we have defined a set of test scenarios that covers a broad range of use cases, in contrast to often used simpler scenes. Our test scenarios include practically relevant scenarios with realistic objects but also synthetic scenes, all of which are available for download. We have evaluated our method in a user study and compared the results to two state-of-the-art selection techniques and the standard ray-based selection. Our results show that LenSelect performs similar to the fastest method, which is ray-based selection, while significantly reducing the error rate by 44%.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

LenSelect: Object Selection in Virtual Environments by Dynamic Object Scaling

Weller

Wegele

Schröder

et al. 2021

Front. Virtual Real.

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“…Manual control was even more challenging when the destination was so far away that the teleportation destination marker (in this study, the green sphere) became invisible and the user had only the distance indicator to rely on. This limitation could be alleviated by providing additional visual guidance and widgets to enhance user's distance estimation [16,39] and performance on selecting distant objects [29]. These issues remain to be studied in future work.…”

Section: Discussionmentioning

confidence: 99%

“…As this study was not about an aided wayfinding task [43], we did not incorporate guidance and visualization techniques for selecting distant targets, such as that done by Mendes et. al [29].…”

Section: Designmentioning

confidence: 98%

Evaluating Automatic Parameter Control Methods for Locomotion in Multiscale Virtual Environments

Lee

Asente

Kim

et al. 2020

26th ACM Symposium on Virtual Reality Software and Technology

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Virtual environments with a wide range of scales are becoming commonplace in Virtual Reality applications. Methods to control locomotion parameters can help users explore such environments more easily. For multi-scale virtual environments, point-and-teleport locomotion with a well-designed distance control method can enable mid-air teleportation, which makes it competitive to flying interfaces. Yet, automatic distance control for point-and-teleport has not been studied in such environments. We present a new method to automatically control the distance for point-and-teleport. In our first user study, we used a solar system environment to compare three methods: automatic distance control for point-and-teleport, manual distance control for point-and-teleport, and automatic speed control for flying. Results showed that automatic control significantly reduces overshoot compared with manual control for pointand-teleport, but the discontinuous nature of teleportation made users prefer flying with automatic speed control. We conducted a second study to compare automatic-speed-controlled flying and two versions of our teleportation method with automatic distance control, one incorporating optical flow cues. We found that pointand-teleport with optical flow cues and automatic distance control was more accurate than flying with automatic speed control, and both were equally preferred to point-and-teleport without the cues. CCS CONCEPTS • Human-centered computing → Human computer interaction (HCI); User studies.

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Fully-Occluded Target Selection in Virtual Reality

Zhou

Newn

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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PRECIOUS! Out-of-reach selection using iterative refinement in VR

Cited by 5 publications

References 11 publications

LenSelect: Object Selection in Virtual Environments by Dynamic Object Scaling

LenSelect: Object Selection in Virtual Environments by Dynamic Object Scaling

Evaluating Automatic Parameter Control Methods for Locomotion in Multiscale Virtual Environments

Fully-Occluded Target Selection in Virtual Reality

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