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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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Closed-form connectivity-preserving solutions for motion compensation using 2-D meshes.

Y Altunbasak¹, A M Tekalp

¹Dept. of Electr. Eng., Rochester Univ., NY.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|January 1, 1997

Summary

This study introduces novel closed-form algorithms for estimating affine motion parameters in 2-D mesh models. These methods enhance motion compensation accuracy and computational efficiency in image processing.

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Area of Science:

Computer Vision
Image Processing
Scientific Computing

Background:

Motion compensation in 2-D mesh models is crucial for image analysis.
Estimating spatial transformation parameters for mesh elements is computationally intensive.
Overdetermined solutions improve robustness but require careful handling of mesh connectivity.

Purpose of the Study:

To develop closed-form, overdetermined solutions for affine motion parameter estimation in triangular meshes.
To present algorithms that preserve mesh connectivity.
To offer computationally efficient alternatives to existing methods.

Main Methods:

Four new algorithms are presented: patch-constrained and node-constrained methods.
Methods utilize either point correspondences or spatio-temporal intensity gradients.
Solutions are derived using least squares estimation.

Main Results:

The proposed closed-form solutions provide accurate affine motion parameter estimation.
Connectivity is preserved through patch-based or node-based constraints.
Performance is comparable to search-based methods with significantly reduced computational cost.

Conclusions:

The developed algorithms offer efficient and robust motion compensation for 2-D triangular meshes.
These methods provide a valuable advancement in image processing and computer vision.
The closed-form solutions balance accuracy and computational efficiency effectively.