Head-related transfer function (HRTF) personalization based on captured images of user
Abstract:
A virtual reality (VR) system simulates sounds that a user of the VR system perceives to have originated from sources at desired virtual locations of the VR system. The simulated sounds are generated based on personalized head-related transfer functions (HRTF) of the user that are constructed by applying machine-learned models to a set of anatomical features identified for the user. The set of anatomical features may be identified from images of the user captured by a camera. In one instance, the HRTF is represented as a reduced set of parameters that allow the machine-learned models to capture the variability in HRTF across individual users while being trained in a computationally-efficient manner.
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