Dynamic HRTF Model Customization via Head-Torso Pose Tracking
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Solution Overview
Problem
Current methods for customizing head-related transfer functions (HRTFs) in audio systems do not account for changes in a user's head position relative to their torso, nor do they break down the HRTF model into customizable components, leading to suboptimal spatial audio experiences.
Innovation Solution
A system dynamically customizes HRTF models by using a template model and applying individualized filters based on the user's pose, including head-torso orientation, to update the HRTF model in real-time, with modifications made at a fast rate and low latency, ensuring accurate sound localization as the user moves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HRTF models are customized for individual users, then sound localization accuracy is improved, but the system complexity increases
Solution Approach 1:
The HRTF model is segmented into static components (anatomical features) and dynamic components (pose-related transformations). This allows the system to maintain personalized sound localization accuracy while reducing complexity by reusing the same static model for multiple users through pose-based dynamic adjustments.
Solution Approach 2:
The system transitions from static HRTF models to dynamic HRTF models that adapt to user pose in real-time. The dynamic component transforms the static HRTF model based on captured pose data, enabling accurate sound localization for each user without requiring complex user-specific models for every possible pose.
2Adaptability or versatility
If HRTF models are updated in real-time to reflect pose changes, then spatial audio experience is improved, but processing latency increases
Solution Approach 1:
The system performs preliminary actions by capturing pose data in advance and pre-computing the dynamic transformations. The pose capture and HRTF update occur before the audio rendering, ensuring that the HRTF model is ready with minimal latency when the audio needs to be spatialized.
Solution Approach 2:
The system maintains continuous updates of the HRTF model as long as the user's pose changes. By continuously monitoring pose and dynamically updating the HRTF model in real-time, the system ensures that the spatial audio experience remains accurate without significant interruptions or delays.
3Ease of operation
If the HRTF model is broken down into customizable components, then ease of customization is improved, but the model complexity increases
Solution Approach 1:
The HRTF model is divided into static and dynamic components, where the static component contains the base anatomical HRTF model and the dynamic component handles pose-related variations. This segmentation makes the model easier to customize by allowing independent modification of each component without affecting the entire model.
Solution Approach 2:
The static HRTF model serves as a universal base that can be applied to multiple users. The dynamic component provides the customization needed for individual users through pose-based transformations. This universality reduces the overall model complexity by avoiding the need to create entirely separate models for each user.
Data Source
AI summary
A system for dynamically updating a head-related transfer function (HRTF) model that is customized to a user. The system receives one or more images of the user captured by one or more imaging devices. The system determines a pose of the user using the one or more captured images. The pose of the user includes a head-torso orientation of the user. The system updates a HRTF model for the user based on the determined pose including the head-torso orientation. The system generates one or more sound filters using the updated HRTF model and applies the one or more sound filters to audio content to generate spatialized audio content. The system provides the spatialized audio content to the user.