A local deviation constraint based non-rigid structure from motion approach

In many traditional non-rigid structure from motion &#x0028 NRSFM &#x0029 approaches, the estimation results of part feature points may significantly deviate from their true values because only the overall estimation error is considered in their models. Aimed at solving this issue, a local d...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2020-09, Vol.7 (5), p.1455-1464
Main Authors: Chen, Xia, Sun, Zhan-Li, Lam, Kin-Man, Zeng, Zhigang
Format: Article
Language:English
Subjects:
Constraints
Deviation
Errors
Estimation
Iterative algorithms
Iterative methods
Lagrange multiplier
Optimization
Rigid structures
Shape
Solid modeling
Strain
Structure from motion
Three-dimensional displays
Two dimensional displays
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Summary:In many traditional non-rigid structure from motion &#x0028 NRSFM &#x0029 approaches, the estimation results of part feature points may significantly deviate from their true values because only the overall estimation error is considered in their models. Aimed at solving this issue, a local deviation-constrained-based column-space-fitting approach is proposed in this paper to alleviate estimation deviation. In our work, an effective model is first constructed with two terms: the overall estimation error, which is computed by a linear subspace representation, and a constraint term, which is based on the variance of the reconstruction error for each frame. Furthermore, an augmented Lagrange multipliers &#x0028 ALM &#x0029 iterative algorithm is presented to optimize the proposed model. Moreover, a convergence analysis is performed with three steps for the optimization process. As both the overall estimation error and the local deviation are utilized, the proposed method can achieve a good estimation performance and a relatively uniform estimation error distribution for different feature points. Experimental results on several widely used synthetic sequences and real sequences demonstrate the effectiveness and feasibility of the proposed algorithm.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2020.1003006