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Updated: Jun 17, 2026
11:28
3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles
Published on: October 1, 2014
Monocular 3-D tracking of inextensible deformable surfaces under L(2) -norm
Shuhan Shen1, Wenhuan Shi, Yuncai Liu
1Institute of Image Processing and Pattern Recognition,Shanghai Jiao Tong University, Shanghai 200240, China. shs@sjtu.edu.cn
Summary
This study introduces a novel method for 3D surface shape recovery from images, improving robustness to noise and outliers using an iterative L(2)-norm approximation for deformable surface tracking.
Area of Science:
- Computer Vision
- Geometric Modeling
- Optimization
Background:
- Recovering 3D shape from monocular image sequences is crucial for various applications.
- Existing methods often rely on L(infinity)-norm, which is sensitive to outliers, and Second-Order Cone Programming (SOCP).
Purpose of the Study:
- To develop a more robust and computationally efficient method for 3D shape recovery of inextensible deformable surfaces.
- To overcome the limitations of L(infinity)-norm sensitivity and nonconvex optimization challenges.
Main Methods:
- Utilizes L(2)-norm of reprojection errors instead of L(infinity)-norm.
- Employs an iterative L(2)-norm approximation process to handle the resulting nonconvex optimization problem.
- Incorporates a shape regularization term to maintain surface inextensibility.
Main Results:
- The proposed method demonstrates improved robustness against image noise, outliers, and large interframe motions.
- Achieves high computational efficiency compared to state-of-the-art techniques.
- Quantitative and qualitative evaluations confirm the approach's accuracy and reliability.
Conclusions:
- The iterative L(2)-norm approximation with shape regularization offers a robust and efficient solution for 3D deformable surface recovery.
- This method provides a significant advancement over traditional L(infinity)-norm-based approaches.
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