Gaitprint Imitation for Visual Tracking Pose Estimation
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Solution Overview
Problem
Current visual tracking systems face challenges in calibrating camera intrinsic parameters under varying operating conditions, which affects the accuracy of pose estimation in augmented and virtual reality applications, and requires significant computational resources and efforts.
Innovation Solution
A method is introduced to transfer a gait pattern from one user to another, allowing for the simulation of augmented reality content in virtual environments, which modifies trajectories based on the gait pattern to generate ground truth data for improving computer vision algorithms, thereby enhancing the calibration of visual tracking systems and reducing resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual tracking systems use standard calibration methods for camera intrinsic parameters, then the system can operate with general-purpose algorithms, but the accuracy of pose estimation deteriorates under varying operating conditions and user-specific motion patterns
Solution Approach 1:
The system performs gait pattern recognition and trajectory modification in advance to generate personalized simulation data before actual visual tracking operations. By pre-processing user-specific gait characteristics and creating customized training datasets, the system prepares adaptive calibration parameters that will improve pose estimation accuracy when deployed, resolving the contradiction between general-purpose operation and user-specific accuracy.
Solution Approach 2:
The system modifies camera intrinsic parameters and trajectory parameters based on recognized gait patterns. By dynamically adjusting these parameters according to user-specific motion characteristics, the system achieves higher pose estimation accuracy for different users while maintaining a general-purpose framework that can adapt to various gait types.
2Measurement precision
If visual tracking systems are calibrated for high accuracy under varying operating conditions, then pose estimation precision improves, but computational resources and calibration efforts increase significantly
Solution Approach 1:
The system creates virtual copies of user trajectories by transferring gait patterns from one user to another through simulation. Instead of collecting and processing extensive real-world calibration data for each user, the system generates synthetic training datasets by copying and adapting gait characteristics, significantly reducing computational resources while maintaining high accuracy through personalized simulation data.
3Reliability
If visual tracking systems collect extensive real-world data for each user, then algorithm personalization improves, but data collection time and system complexity increase
Solution Approach 1:
The system introduces a gait pattern recognition module and trajectory simulation engine as intermediaries between raw sensor data and personalized algorithms. These intermediary components extract essential gait characteristics and generate synthetic training data, eliminating the need for extensive direct data collection while achieving effective algorithm personalization through simulated user-specific trajectories.
Data Source
AI summary
A method for transferring a gait pattern of a first user to a second user to simulate augmented reality content in a virtual simulation environment is described. In one aspect, the method includes identifying a gait pattern of a first user operating a first visual tracking system in a first physical environment, identifying a trajectory from a second visual tracking system operated by a second user in a second physical environment, the trajectory based on poses of the second visual tracking system over time, modifying the trajectory from the second visual tracking system based on the gait pattern of the first user, applying the modified trajectory in a plurality of virtual environments, and generating simulated ground truth data based on the modified trajectory in the plurality of virtual environments.