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EMMCVPR
1999
Springer
13 years 11 months ago
Maximum Likelihood Inference of 3D Structure from Image Sequences
The paper presents a new approach to recovering the 3D rigid shape of rigid objects from a 2D image sequence. The method has two distinguishing features: it exploits the rigidity o...
Pedro M. Q. Aguiar, José M. F. Moura
ICCV
2005
IEEE
14 years 9 months ago
Shape Recovery of 3D Data Obtained from a Moving Range Sensor by Using Image Sequences
For a large object, scanning from the air is one of the most efficient methods of obtaining 3D data. But in the case of large cultural heritage objects, there are some difficultie...
Atsuhiko Banno, Katsushi Ikeuchi
IJCV
2010
169views more  IJCV 2010»
13 years 6 months ago
Rigid Structure from Motion from a Blind Source Separation Perspective
We present an information theoretic approach to define the problem of structure from motion (SfM) as a blind source separation one. Given that for almost all practical joint densi...
Jeff Fortuna, Aleix M. Martínez
ICCV
2011
IEEE
12 years 7 months ago
A Theory of Coprime Blurred Pairs
We present a new Coprime Blurred Pair (CBP) theory that may benefit a number of computer vision applications. A CBP is constructed by blurring the same latent image with two unkn...
Feng Li, Zijia Li, David Saunders, Jingyi Yu
CVPR
2004
IEEE
14 years 9 months ago
3D Human Pose from Silhouettes by Relevance Vector Regression
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pr...
Ankur Agarwal, Bill Triggs