Sequential Non-Rigid Structure from Motion Using Physical Priors
نویسندگان
چکیده
منابع مشابه
Sequential Bayesian Non-Rigid Structure from Motion
This thesis1 addresses the problem of recovering simultaneously camera motion and the 3D reconstruction of deformable objects from monocular video. We propose several methods to solve this problem in a sequential fashion, frame-by-frame estimation, as the data arrives. Deformable structures appear constantly in our everyday life, from human non-rigid motion (e.g., a smiling face or performing d...
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This paper describes how the generalization ability of methods for non-rigid Structure-from-Motion can be improved by using priors. Most point tracks are often visible only in some of the images; predicting the missing data can be important. Previous Maximum-Likelihood (ML)-approaches on implicit non-rigid Structure-from-Motion generalize badly. Although the estimated model fits well to the vis...
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Reconstructing a 3D deformable surface from a set of 2D correspondences across an image sequence is the problem known as Non-Rigid Structure from Motion (NRSfM). In this scenario, it is usually assumed that the 3D deformable shape can be represented by a combination of rigid basis shapes with time varying coefficients. Due to its simplicity, linear basis shape models have provided good reconstr...
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Recovering deformable 3D motion from temporal 2D point tracks in a monocular video is an open problem with many everyday applications throughout science and industry, or the new augmented reality. Recently, several techniques have been proposed to deal the problem called Non-Rigid Structure from Motion (NRSfM), however, they can exhibit poor reconstruction performance on complex motion. In this...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2016
ISSN: 0162-8828,2160-9292
DOI: 10.1109/tpami.2015.2469293