Publication
Sequential non-rigid structure from motion using physical priors
Journal Article (2016)
Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pages
979-994
Volume
38
Number
5
Doc link
http://dx.doi.org/10.1109/TPAMI.2015.2469293
File
Authors
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Agudo Martínez, Antonio
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Moreno Noguer, Francesc
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Calvo, Begoña
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Martínez Montiel, José María
Projects associated
Abstract
We propose a new approach to simultaneously recover camera pose and 3D shape of non-rigid and potentially extensible surfaces from a monocular image sequence. For this purpose, we make use of the EKF-SLAM (Extended Kalman Filter based Simultaneous Localization And Mapping) formulation, a Bayesian optimization framework traditionally used in mobile robotics for estimating camera pose and reconstructing rigid scenarios. In order to extend the problem to a deformable domain we represent the object’s surface mechanics by means of Navier’s equations, which are solved using a FEM (Finite Element Method). With these main ingredients, we can further model the material’s stretching, allowing us to go a step further than most of current techniques, typically constrained to surfaces undergoing isometric deformations. We extensively validate our approach in both real and synthetic experiments, and demonstrate its advantages with respect to competing methods. More specifically, we show that besides simultaneously retrieving camera pose and non-rigid shape, our approach is adequate for both isometric and extensible surfaces, does not require neither batch processing all the frames nor tracking points over the whole sequence and runs at several frames per second.
Categories
computer vision.
Scientific reference
A. Agudo, F. Moreno-Noguer, B. Calvo and J.M. Martínez. Sequential non-rigid structure from motion using physical priors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(5): 979-994, 2016.
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