Monocular 3D Pose Estimation Reliability Evaluation by Rotation
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Solution Overview
Problem
The performance evaluation of three-dimensional (3D) pose estimation models is challenging due to environmental differences between training and deployment, and the lack of ground truth for keypoints, making it difficult to determine the suitability of these models for specific applications.
Innovation Solution
An apparatus and method for evaluating the reliability of a human pose estimation algorithm using a monocular image, which involves capturing images of a person in specific poses or motions, estimating body information, and calculating consistency and similarity indicators to assess the algorithm's performance without requiring separate ground truth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a 3D pose estimation model is evaluated in a different environment from its training environment, then the model's adaptability is improved, but the measurement precision of pose estimation deteriorates
Solution Approach 1:
The patent implements a feedback mechanism by capturing actual pose data from the target object in the deployment environment and comparing it with the estimated pose data. The system calculates evaluation metrics (such as mean per joint position error) based on this comparison, providing feedback on the model's performance in the specific environment, which can then be used to fine-tune or retrain the model for improved precision while maintaining environmental adaptability.
Solution Approach 2:
The patent changes the evaluation parameters by using multiple viewpoint images and calculating pose estimation accuracy from different angles. By evaluating the model's performance across multiple parameters (different viewpoints, different body parts), the system achieves a more comprehensive assessment that accounts for environmental variations while maintaining measurement precision through multi-dimensional validation.
2Ease of operation
If ground truth data is not available for evaluation, then the ease of operation is improved, but the measurement precision deteriorates
Solution Approach 1:
The patent implements a self-service evaluation mechanism where the system captures images of the target object in its natural environment, estimates the pose from these images, and then compares the estimated pose with actual pose data captured from the same images. This self-contained evaluation process eliminates the need for external ground truth data or specialized measurement equipment, maintaining ease of operation while ensuring measurement precision through direct comparison with actual captured data.
Solution Approach 2:
The patent uses captured images as an intermediary to bridge the gap between estimated pose and actual pose. By capturing images that contain both the target object and reference information, the system uses these images as a mediator to extract both the estimated pose (through the pose estimation model) and the actual pose (through image processing), enabling accurate evaluation without requiring separate ground truth data sources.
3Measurement precision
If multiple cameras are used to capture images for pose estimation, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent transitions from spatial dimensionality (multiple cameras) to temporal dimensionality (multiple frames from a single camera). By capturing a sequence of images over time and processing them through the pose estimation model, the system achieves accurate 3D pose estimation using a single camera, thereby reducing device complexity while maintaining or improving measurement precision through temporal information integration.
Solution Approach 2:
The patent makes the single camera perform multiple functions by capturing images that serve both as input for the pose estimation model and as reference data for evaluation. The captured images are used universally for both estimating the pose and verifying its accuracy, eliminating the need for separate camera systems and reducing overall device complexity while maintaining measurement precision.
Data Source
AI summary
According to the present invention, an apparatus for evaluating reliability of a human pose estimation algorithm for estimating a human three-dimensional (3D) pose based on a monocular image includes a memory configured to store at least one instruction; and a processor configured to execute the at least one instruction stored in the memory, in which the processor acquires a first image obtained by capturing an image of a person rotating in a preset specific pose with a single camera, performs a process of estimating first body information of the person from the first image using a target human pose estimation algorithm for each frame, and evaluates reliability of the target human pose estimation algorithm based on the first body information estimated for each frame.