Abstract
The problem of 3D reconstruction of nonrigid objects from uncalibrated image sequences is addressed in the paper. Our method assumes that the nonrigid object is composed of rigid part and deformation part. We first recover the affine structure of the object and separate the rigid features from the deformation ones. Then stratify the structure from affine to Euclidean space by virtue of the rigid features. The novelty of the paper lies in two aspects. First, we propose a deformation weight constraint to the problem and prove that the recovered shape bases and shapes are transformation invariant under this constraint. Second, we propose a constrained power factorization (CPF) algorithm to recover the deformation structure in affine space. The algorithm overcomes the limitations of previous SVD-based methods and can work with missing data in the tracking matrix. Extensive experiments on synthetic data and real sequences validate the proposed method and show improvements over existing solutions.
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Wang, G., Wu, Q.M.J. (2007). Deformation Weight Constraint and 3D Reconstruction of Nonrigid Objects. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_26
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DOI: https://doi.org/10.1007/978-3-540-74260-9_26
Publisher Name: Springer, Berlin, Heidelberg
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