VR Headset Tracking Using IMU and Camera Blur Detection
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Solution Overview
Problem
Current virtual reality tracking technologies often fail to accurately measure user head movements, leading to discomfort and motion sickness due to inexact tracking, especially under conditions of image blur or noisy inertial sensor data.
Innovation Solution
A movement tracking system comprising a camera, inertial measurement unit (IMU) sensor, and processor that calculates the moving distance of a head-mounted display by combining frame information with IMU data, determining blurred pixels, and generating frame content accordingly to ensure precise tracking and reduce motion blur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tracking technology uses inertial sensors and camera images to measure head movements, then the tracking coverage and adaptability are improved, but the measurement precision deteriorates due to image blur and noisy sensor data
Solution Approach 1:
The patent introduces an intermediary processing system that mediates between the camera images and inertial sensor data. The processor combines information from both sources, using the inertial sensor data to compensate for image blur and provide continuous tracking even when visual data is degraded, thus maintaining measurement precision while preserving tracking coverage
Solution Approach 2:
The patent merges data from multiple sources (camera images and inertial sensors) into a unified tracking system. By combining visual tracking with inertial measurement, the system achieves both broad adaptability and maintained precision, as the inertial data compensates for weaknesses in visual tracking under blur conditions
2Productivity
If the camera captures frames at high speed to reduce motion blur, then the productivity is improved, but the use of energy increases
Solution Approach 1:
The patent applies partial action by using inertial sensor data to supplement frame capture only when necessary (e.g., during rapid movement or when blur is detected). This allows the system to maintain high effective frame rates for tracking accuracy without continuously capturing and processing high-speed video frames, thus reducing energy consumption while preserving productivity
Solution Approach 2:
The system performs preliminary action by using inertial sensors to predict head movement and pre-compensate for potential blur conditions. This allows the processor to generate accurate tracking data without always requiring high-speed frame capture, reducing energy usage while maintaining effective productivity
Data Source
Figure 1A~1B
Figure 2
Figure 3A~3B
AI summary
One aspect of the present disclosure is related to a movement tracking method for an electronic apparatus. The movement tracking method for an electronic apparatus comprises: obtaining information of a first frame captured by a camera; obtaining (inertial measurement unit) IMU information from an IMU sensor; calculating a first blurred pixel parameter of the first frame according to the information of the first frame and the IMU information by a processor; and determining whether the first blurred pixel parameter of the first frame is smaller than a blur threshold or not by the processor; if the first blurred pixel parameter of the first frame is smaller than the blur threshold, calculating a movement data of the electronic apparatus according to the information of the first frame and the IMU information.