HMD Pose Estimation via Inverse Kinematics and 6 DoF Tracking
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Solution Overview
Problem
Conventional head-mounted display (HMD) devices lack inherent functionality for accurately detecting a user's pose, relying on separate sensors which are inconvenient and costly.
Innovation Solution
An HMD device equipped with at least two cameras, such as fisheye cameras, and an inertial sensor, capable of estimating a user's pose by obtaining images of their body and head, applying inverse kinematics and 6 degrees of freedom tracking to determine the user's overall pose without external sensing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate sensors or motion capture suits are used to detect user pose, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent merges the pose detection functionality into the HMD device itself by integrating cameras and sensors that are already part of the HMD structure. The system uses images captured by HMD cameras and data from HMD sensors (accelerometer, gyroscope, magnetometer) to estimate user pose, eliminating the need for separate motion capture suits or external sensing devices.
Solution Approach 2:
The HMD device is designed to serve multiple functions: it provides virtual/augmented reality display while simultaneously performing pose detection using its existing cameras and sensors. The inertial measurement unit (IMU) and cameras originally intended for other HMD functions are repurposed to detect user pose, making the device multi-functional without requiring additional specialized equipment.
2Measurement precision
If separate sensors or motion capture suits are used to detect user pose, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent merges the pose detection functionality into the HMD device itself by integrating cameras and sensors that are already part of the HMD structure. The system uses images captured by HMD cameras and data from HMD sensors (accelerometer, gyroscope, magnetometer) to estimate user pose, eliminating the need for separate motion capture suits or external sensing devices.
Solution Approach 2:
The HMD device performs pose detection using its own built-in resources (cameras and inertial sensors) without requiring external assistance. The device serves itself by utilizing its existing hardware components for dual purposes: providing VR/AR display and detecting user pose, thereby eliminating the need for additional paid equipment.
3Measurement precision
If separate sensing devices are used to detect user pose, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent merges the pose detection functionality into the HMD device itself by integrating cameras and sensors that are already part of the HMD structure. The system uses images captured by HMD cameras and data from HMD sensors (accelerometer, gyroscope, magnetometer) to estimate user pose, eliminating the need for separate motion capture suits or external sensing devices.
Solution Approach 2:
The HMD device performs pose detection using its own built-in resources (cameras and inertial sensors) without requiring external assistance. The device serves itself by utilizing its existing hardware components for dual purposes: providing VR/AR display and detecting user pose, thereby eliminating the need for additional paid equipment.
Data Source
AI summary
A method for estimating a pose of a user by a head-mounted display (HMD) device is provided. The method includes obtaining at least two images from at least two cameras of the HMD device, each of the at least two obtained images including a view of at least a portion of a body of the user wearing the HMD device, estimating a pose of the body of the user based on the view of the at least portion of the body of the user included in each of the at least two obtained images, estimating a pose of a head of the user based on the at least two obtained images, and estimating the pose of the user based on the estimated pose of the body of the user and the estimated pose of the head of the user.