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May 31
02:55 PM - 03:20 PM
Description
Doublepoint builds a gesture-based touch interface to enable efficient, robust, and intuitive AR interaction. At this talk, they will showcase how these solutions can work as standalone input modalities or be combined to supercharge eye tracking and hand tracking.
User input is one of the many challenges standing in the way of the mass adoption of AR. How will the everyday person interact in Augmented Reality? What's the role of touch in interaction? At Doublepoint we research different ways for people to interact in AR and develop the best technologies to detect these interactions efficiently and reliably.
Currently, there are a lot of input methods for AR using built-in sensors of the headset, such as hand tracking, eye tracking, and voice input. However, if we want it to be as transformative as the graphical user interface or the capacitive touch screen, we need to put deliberate thought into building the ideal input paradigm and the needed hardware that might not be in the headset itself.
At this talk:
• We’ll demonstrate how a machine learning algorithm on existing smartwatches can already significantly improve AR interaction.
• We’ll show how it can be combined with eye tracking and hand tracking sensors in the headset to improve interactions even more.
• Lastly, we'll show some of our future custom hardware dedicated to sensing advanced micro-gestures in a small and convenient form factor.
Speakers
Co-Founder and CTO
,
Doublepoint
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