Results 291 to 300 of about 7,192,578 (342)

Odometry-Based Structure from Motion

2007 IEEE Intelligent Vehicles Symposium, 2007
Structure from motion refers to a technique to obtain 3D information from consecutive images taken with a moving monocular camera. In order to do this, the camera motion performed between two consecutive images needs to be known. In the work reported in this contribution, we investigated the precision of the odometry data of a commercially available ...
Grinberg, M., Woock, P., Pagel, F., Willersinn, D.   +3 more
openaire   +1 more source

Global Structure-from-Motion Revisited

European Conference on Computer Vision
Recovering 3D structure and camera motion from images has been a long-standing focus of computer vision research and is known as Structure-from-Motion (SfM). Solutions to this problem are categorized into incremental and global approaches. Until now, the
Linfei Pan, Dániel Baráth, M. Pollefeys, Johannes L. Schönberger   +3 more
semanticscholar   +1 more source

Structure From Motion on XSlit Cameras

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
We present a structure-from-motion (SfM) framework based on a special type of multi-perspective camera called the cross-slit or XSlit camera. Traditional perspective camera based SfM suffers from the scale ambiguity which is inherent to the pinhole camera geometry. In contrast, an XSlit camera captures rays passing through two oblique lines in 3D space
Wei, Yang, Yingliang, Zhang, Jinwei, Ye, Yu, Ji, Zhong, Li, Mingyuan, Zhou, Jingyi, Yu   +6 more
openaire   +2 more sources

MASt3R-SfM: A Fully-Integrated Solution for Unconstrained Structure-from-Motion

International Conference on 3D Vision
Structure-from-Motion (SfM), a task aiming at jointly recovering camera poses and 3D geometry of a scene given a set of images, remains a hard problem with still many open challenges despite decades of significant progress.
B. Duisterhof, Lojze Žust, Philippe Weinzaepfel, Vincent Leroy, Yohann Cabon, Jérôme Revaud   +5 more
semanticscholar   +1 more source

DeepSFM: Structure From Motion Via Deep Bundle Adjustment

European Conference on Computer Vision, 2019
Structure from motion (SfM) is an essential computer vision problem which has not been well handled by deep learning. One of the promising trends is to apply explicit structural constraint, e.g. 3D cost volume, into the network. However, existing methods
Xingkui Wei, Yinda Zhang, Zhuwen Li, Yanwei Fu, X. Xue   +4 more
semanticscholar   +1 more source

Photogrammetry is for everyone: Structure-from-motion software user experiences in archaeology

, 2020
In this study, Structure-from-Motion (SfM) photogrammetric software was used to create 3D models of the Tyler house (Mound, TX) and Eyrie house (Holyoke, MA), both mid-19th century ruins.
Christine Jones, E. Church
semanticscholar   +1 more source

Structure from motion

2010
In the previous chapter, we saw how 2D and 3D point sets could be aligned and how such alignments could be used to estimate both a camera’s pose and its internal calibration parameters. In this chapter, we look at the converse problem of estimating the locations of 3D points from multiple images given only a sparse set of correspondences between image ...
openaire   +2 more sources

Bayesian structure from motion

Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999
Formulates 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.
D.A. Forsyth, S. Ioffe, J. Haddon
openaire   +1 more source

Semantic structure from motion

CVPR 2011, 2011
Conventional 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 Yingze Bao, Silvio Savarese
openaire   +1 more source

Reducing "structure from motion"

Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996
The 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
openaire   +2 more sources