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Modelling Nonrigid Object from Video Sequence Under Perspective Projection

机译:透视投影下基于视频序列的非刚性对象建模

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摘要

The paper is focused on the problem of estimating 3D structure and motion of nonrigid object from a monocular video sequence. Many previous methods on this problem utilize the extension technique of factorization based on rank constraint to the tracking matrix, where the 3D shape of nonrigid object is expressed as weighted combination of a set of shape bases. All these solutions are based on the assumption of affine camera model. This assumption will become invalid and cause large reconstruction errors when the object is close to the camera. The main contribution of this paper is that we extend these methods to the general perspective camera model. The proposed algorithm iter-atively updates the shape and motion from weak perspective projection to fully perspective projection by refining the scalars corresponding to the projective depths. Extensive experiments on real sequences validate the effectiveness and improvements of the proposed method.
机译:本文着重于从单眼视频序列估计3D结构和非刚性物体运动的问题。关于这个问题的许多先前方法利用基于秩约束的分解技术对跟踪矩阵的扩展技术,其中非刚性对象的3D形状表示为一组形状基准的加权组合。所有这些解决方案均基于仿射相机模型的假设。当物体靠近相机时,此假设将变得无效并导致较大的重建错误。本文的主要贡献在于,我们将这些方法扩展到了通用透视相机模型。所提算法通过细化对应于投影深度的标量,迭代地将形状和运动从弱视点投影更新为全视点投影。在真实序列上的大量实验验证了所提方法的有效性和改进。

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