開始時刻
前のセッションの直後
139. Perception and Input in Immersive Environments
発表数
5
時間
3分
発表担当
目次
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Big or Small, It’s All in Your Head: Visuo-Haptic Illusion of Size-Change Using Finger-Repositioning
説明
Haptic perception of physical sizes increases the realism and immersion in Virtual Reality (VR). Prior work rendered sizes by exerting pressure on the user’s fingertips or employing tangible, shape-changing devices. These interfaces are constrained by the physical shapes they can assume, making it challenging to simulate objects growing larger or smaller than the perceived size of the interface. Motivated by literature on pseudo-haptics describing the strong influence of visuals over haptic perception, this work investigates modulating the perception of size beyond this range. We developed a fixed-sized VR controller leveraging finger-repositioning to create a visuo-haptic illusion of dynamic size-change of handheld virtual objects. Through two user studies, we found that with an accompanying size-changing visual context, users can perceive virtual object sizes up to 44.2% smaller to 160.4%larger than the perceived size of the device. Without the accompanying visuals, a constant size (141.4% of device size) was perceived.
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STMG: A Machine Learning Microgesture Recognition System for Supporting Thumb-Based VR/AR Input
説明
AR/VR devices have started to adopt hand tracking, in lieu of controllers, to support user interaction. However, today's hand input rely primarily on one gesture: pinch. Moreover, current mappings of hand motion to use cases like VR locomotion and content scrolling involve more complex and larger arm motions than joystick or trackpad usage. STMG increases the gesture space by recognizing additional small thumb-based microgestures from skeletal tracking running on a headset. We take a machine learning approach and achieve a 95.1% recognition accuracy across seven thumb gestures performed on the index finger surface: four directional thumb swipes (left, right, forward, backward), thumb tap, and fingertip pinch start and pinch end. We detail the components to our machine learning pipeline and highlight our design decisions and lessons learned in producing a well generalized model. We then demonstrate how these microgestures simplify and reduce arm motions for hand-based locomotion and scrolling interactions.
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Beyond the Blink: Investigating Combined Saccadic & Blink-Suppressed Hand Redirection in Virtual Reality
説明
In pursuit of hand redirection techniques that are ever more tailored to human perception, we propose the first algorithm for hand redirection in virtual reality that makes use of saccades, i.e., fast ballistic eye movements that are accompanied by the perceptual phenomenon of change blindness. Our technique combines the previously proposed approaches of gradual hand warping and blink-suppressed hand redirection with the novel approach of saccadic redirection in one unified yet simple algorithm. We compare three variants of the proposed Saccadic & Blink-Suppressed Hand Redirection (SBHR) technique with the conventional approach to redirection in a psychophysical study (N=25). Our results highlight the great potential of our proposed technique for comfortable redirection by showing that SBHR allows for significantly greater magnitudes of unnoticeable redirection while being perceived as significantly less intrusive and less noticeable than commonly employed techniques that only use gradual hand warping.
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TriPad: Touch Input in AR on Ordinary Surfaces with Hand Tracking Only
説明
TriPad enables opportunistic touch interaction in Augmented Reality using hand tracking only. Users declare the surface they want to appropriate with a simple hand tap gesture. They can then use this surface at will for direct and indirect touch input. TriPad only involves analyzing hand movements and postures, without the need for additional instrumentation, scene understanding or machine learning. TriPad thus works on a variety of flat surfaces, including glass. It also ensures low computational overhead on devices that typically have a limited power budget. We describe the approach, and report on two user studies. The first study demonstrates the robustness of TriPad's hand movement interpreter on different surface materials. The second study compares TriPad against direct mid-air AR input techniques on both discrete and continuous tasks and with different surface orientations. TriPad achieves a better speed-accuracy trade-off overall, improves comfort and minimizes fatigue.
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Flicker Augmentations: Rapid Brightness Modulation for Real-World Visual Guidance using Augmented Reality
説明
Providing attention guidance, such as assisting in search tasks, is a prominent use for Augmented Reality. Typically, this is achieved by graphically overlaying geometrical shapes such as arrows. However, providing visual guidance can cause side effects such as attention tunnelling or scene occlusions, and introduce additional visual clutter. Alternatively, visual guidance can adjust saliency but this comes with different challenges such as hardware requirements and environment dependent parameters. In this work we advocate for using flicker as an alternative for real-world guidance using Augmented Reality. We provide evidence for the effectiveness of flicker from two user studies. The first compared flicker against alternative approaches in a highly controlled setting, demonstrating efficacy (N = 28). The second investigated flicker in a practical task, demonstrating feasibility with higher ecological validity (N = 20). Finally, our discussion highlights the opportunities and challenges when using flicker to provide real-world visual guidance using Augmented Reality.
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