2020
DOI: 10.1109/tvcg.2020.3023606
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Fully-Occluded Target Selection in Virtual Reality

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Cited by 46 publications
(20 citation statements)
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References 72 publications
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“…The computing component collects sensor data and determines what is displayed on the screen [20]. During physical rehabilitation, the patient's body shape change and position movement must be captured by the motion tracking sensor and simultaneously transmitted to the virtual object in VR [21]. Sensors that track patient motion must have accessories with motion visualization functions, including mice, joystick, depth-sensing cameras [22], electromagnetic sensors [23], inertial sensors, bending sensors, and data gloves.…”
Section: Vr Equipmentmentioning
confidence: 99%
“…The computing component collects sensor data and determines what is displayed on the screen [20]. During physical rehabilitation, the patient's body shape change and position movement must be captured by the motion tracking sensor and simultaneously transmitted to the virtual object in VR [21]. Sensors that track patient motion must have accessories with motion visualization functions, including mice, joystick, depth-sensing cameras [22], electromagnetic sensors [23], inertial sensors, bending sensors, and data gloves.…”
Section: Vr Equipmentmentioning
confidence: 99%
“…shaking hands). As such, researchers have developed a variety of target disambiguation techniques that requires additional manual steps for final selection [5,23,35,77] or that apply contextual information or heuristics for implicit disambiguation [23,24,60,68]. However, while these techniques help users perform difficult selections, many assume a stable signal to disambiguate target candidates.…”
Section: Refinement and Disambiguationmentioning
confidence: 99%
“…Further research needs to be done to evaluate the techniques in more natural settings. Occlusion is interesting to investigate as targets are closely placed together, and occlusion lessens the effective target width making interaction more difficult, especially with noisy data [66,77]. The impact of data noise on interaction has to be further investigated within applications and natural environments beyond controlled lab environments.…”
Section: Limitationsmentioning
confidence: 99%
“…Multi-perspective visualization. The multi-perspective vision is characterized by transforming an alternative view into the main window [64,71]. Prior studies captured occluded regions from the secondary perspective and integrated them seamlessly into the user's view [61,70].…”
Section: See-through Visionmentioning
confidence: 99%