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IEEE Transactions on Image Processing, 2006
Planar motion is arguably the most dominant type of motion in surveillance videos. The constraints on motion lead to a simplified factorization method for structure from planar motion when using a stationary perspective camera. Compared with methods for general motion, our approach has two major advantages: a measurement matrix that fully exploits the ...
Jian Li 0022, Rama Chellappa
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Planar motion is arguably the most dominant type of motion in surveillance videos. The constraints on motion lead to a simplified factorization method for structure from planar motion when using a stationary perspective camera. Compared with methods for general motion, our approach has two major advantages: a measurement matrix that fully exploits the ...
Jian Li 0022, Rama Chellappa
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Journal of the Optical Society of America A, 1991
A mobile observer samples sequences of narrow-field projections of configurations in ambient space. The so-called structure-from-motion problem is to infer the structure of these spatial configurations from the sequence of projections. For rigid transformations, a unique metrical reconstruction is known to be possible from three orthographic views of ...
J J, Koenderink, A J, van Doorn
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A mobile observer samples sequences of narrow-field projections of configurations in ambient space. The so-called structure-from-motion problem is to infer the structure of these spatial configurations from the sequence of projections. For rigid transformations, a unique metrical reconstruction is known to be possible from three orthographic views of ...
J J, Koenderink, A J, van Doorn
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Structure from Motion with Objects
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016This paper shows for the first time that is possible to reconstruct the position of rigid objects and to jointly recover affine camera calibration solely from a set of object detections in a video sequence. In practice, this work can be considered as the extension of Tomasi and Kanade factorization method using objects.
Marco Crocco +2 more
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Structure from controlled motion
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996This paper deals with the recovery of 3D information using a single mobile camera in the context of active vision. First, we propose a general revisited formulation of the structure-from-known-motion issue. Within the same formalism, we handle various kinds of 3D geometrical primitives such as points, lines, cylinders, spheres, etc.
François Chaumette +3 more
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2014 IEEE International Conference on Computational Photography (ICCP), 2014
In outdoor images, cast shadows define 3D constraints between the sun, the points casting a shadow, and the surfaces onto which shadows are cast. This cast shadow structure provides a powerful cue for 3D reconstruction, but requires that shadows be tracked over time, and this is difficult as shadows have minimal texture.
Austin Abrams +2 more
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In outdoor images, cast shadows define 3D constraints between the sun, the points casting a shadow, and the surfaces onto which shadows are cast. This cast shadow structure provides a powerful cue for 3D reconstruction, but requires that shadows be tracked over time, and this is difficult as shadows have minimal texture.
Austin Abrams +2 more
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Reducing "structure from motion"
Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of different models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction.
Soatto, Stefano, Perona, Pietro
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Bayesian structure from motion
Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999Formulates structure from motion as a Bayesian inference problem and uses a Markov-chain Monte Carlo sampler to sample the posterior on this problem. This results in a method that can identify both small and large tracker errors and yields reconstructions that are stable in the presence of these errors.
David A. Forsyth +2 more
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Semantic structure from motion
CVPR 2011, 2011Conventional rigid structure from motion (SFM) addresses the problem of recovering the camera parameters (motion) and the 3D locations (structure) of scene points, given observed 2D image feature points. In this paper, we propose a new formulation called Semantic Structure From Motion (SSFM).
Sid Ying-Ze Bao, Silvio Savarese
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Recursive Structure from Motion
2017In this paper we present a technique that estimates the Structure from Motion (SFM) in a recursive fashion. Traditionally successful SFM algorithms take the set of images and estimate the scene geometry and camera positions either using incremental algorithms or the global algorithms and do the refinement process [2] to reduce the reprojection error ...
M. Chebiyyam +2 more
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Structure-from-Motion Revisited
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016Incremental Structure-from-Motion is a prevalent strategy for 3D reconstruction from unordered image collections. While incremental reconstruction systems have tremendously advanced in all regards, robustness, accuracy, completeness, and scalability remain the key problems towards building a truly general-purpose pipeline.
Johannes L. Schönberger +1 more
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