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Robust Structure and Motion Recovery Based on Augmented Factorization
Wang, Guanghui
Wang, Guanghui
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Abstract
This paper proposes a new strategy to promote the robustness of structure from motion algorithm from uncalibrated video sequences. First, an augmented affine factorization algorithm is formulated to circumvent the difficulty in image registration with noise and outliers contaminated data. Then, an alternative weighted factorization scheme is designed to handle the missing data and measurement uncertainties in the tracking matrix. Finally, a robust strategy for structure and motion recovery is proposed to deal with outliers and large measurement noise. This paper makes the following main contributions: 1) An augmented factorization algorithm is proposed to circumvent the difficult image registration problem of previous affine factorization, and the approach is applicable to both rigid and nonrigid scenarios; 2) by employing the fact that image reprojection residuals are largely proportional to the error magnitude in the tracking data, a simple outliers detection approach is proposed; and 3) a robust factorization strategy is developed based on the distribution of the reprojection residuals. Furthermore, the proposed approach can be easily extended to nonrigid scenarios. Experiments using synthetic and real image data demonstrate the robustness and efficiency of the proposed approach over previous algorithms.
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Date
2017-09-21
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Publisher
Institute of Electrical and Electronics Engineers
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Keywords
Structure and motion factorization, Robust factorization, Alternative factorization, Outlier detection, Reprojection residual, Robustness, Tracking, Matrix decomposition, Three-dimensional displays, Algorithm design and analysis, Cameras, Shape
Citation
G. Wang, "Robust Structure and Motion Recovery Based on Augmented Factorization," in IEEE Access, vol. 5, pp. 18999-19011, 2017. doi: 10.1109/ACCESS.2017.2755019