3D Pose Estimation Using Relative Depth Ambiguity Resolution
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Solution Overview
Problem
Existing methods for estimating the three-dimensional pose of objects from images suffer from ambiguity in depth estimation, leading to decreased accuracy due to unclear reference points for relative depth calculation.
Innovation Solution
A three-dimensional pose estimation method that assumes multiple relative positions for each pair of control points defining an object's skeleton, estimating relative depth with respect to one control point across the image, and using these estimates to detect two-dimensional positions and calculate relative three-dimensional positions of control points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If relative depth is estimated without specifying reference positions, then the estimation process is simpler, but the depth estimation becomes ambiguous and accuracy decreases
Solution Approach 1:
The patent performs preliminary action by pre-defining multiple candidate reference positions for each control point before estimating relative depth. This preliminary specification of reference positions eliminates ambiguity during the depth estimation process, ensuring that each control point has a clear reference framework while maintaining systematic processing flow.
Solution Approach 2:
The patent segments the depth estimation process by handling each control point independently with its own set of candidate reference positions. This segmentation allows the system to process depth estimation in discrete, manageable units, where each control point's depth is estimated relative to its specific reference positions without interfering with other control points.
2Measurement precision
If multiple candidate reference positions are defined for each control point, then depth estimation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by considering only the necessary candidate reference positions for each control point rather than exhaustively evaluating all possible positions. The system defines a limited set of candidate reference positions that are sufficient for accurate depth estimation, avoiding unnecessary computational overhead while maintaining precision.
Solution Approach 2:
The patent uses copying by creating a standardized template of candidate reference positions that can be reused for different control points. This template-based approach allows the system to efficiently generate reference frameworks for multiple control points without recompute from scratch, reducing overall computational complexity.
3Productivity
If depth is estimated relative to unspecified positions, then the estimation process is faster, but ambiguity reduces estimation accuracy
Solution Approach 1:
The patent performs preliminary action by pre-establishing candidate reference positions before the main depth estimation process. This allows the estimation to proceed efficiently using predefined references rather than performing complex real-time reference determination, thus maintaining speed while improving accuracy through clear reference specifications.
Solution Approach 2:
The patent changes the parameter of reference position specification from undefined to multiple candidate positions. This parameter change enables the system to maintain fast processing by using predefined reference frameworks while significantly improving depth estimation accuracy through explicit reference position identification.
Data Source
AI summary
A method for estimating a three-dimensional pose from control points of an image of the object, includes: selecting, for each pair consisting of first and second control points that define a skeleton of the object, relative positions of the first control point with respect to the second control point on the image, estimating, for each of the selected relative positions, a relative depth of the first control point with respect to the second control point over the entire image based on an assumption that the second control point exists at each position on the image; detecting two-dimensional positions of the control points on the image for the object using the image; obtaining, based on the relative depth estimated for each of the selected relative positions and the two-dimensional positions of the control points, relative three-dimensional positions of the control points; and estimating the three-dimensional pose for the object.