Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Fangda, Zhao"'
Publikováno v:
in Proc. of MIRU2018
We propose an easy-to-use non-overlapping camera calibration method. First, successive images are fed to a PoseNet-based network to obtain ego-motion of cameras between frames. Next, the pose between cameras are estimated. Instead of using a batch me
Externí odkaz:
http://arxiv.org/abs/2002.08005
Publikováno v:
Image and Vision Computing. 70:46-54
Simple methods to calibrate non-overlapping cameras using markers on the cameras are proposed. By adding an augmented reality (AR) marker to a camera, we can find the transformation between the fixed AR marker and the camera. With such information, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2843cb2b954889c1ccf26847768212d3
https://doi.org/10.1016/j.imavis.2017.12.006
https://doi.org/10.1016/j.imavis.2017.12.006
Publikováno v:
Neural Computing and Applications. 29:1209-1224
3D point clouds are important for the reconstruction of environment. However, comparing to the artificial VR scene representation methods, 3D point clouds are more difficult to correspond to real scenes. In this paper, a method for detecting keypoint
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30d299d84fba60d64a4e8edc7cfa2fa0
https://doi.org/10.1007/s00521-017-2964-1
https://doi.org/10.1007/s00521-017-2964-1
Publikováno v:
Machine Vision and Applications. 25:1989-2002
In this paper, we propose two methods for estimating the scales of point clouds to align them. The first method estimates the scale of each point cloud separately: each point cloud has its own scale that is something like the size of a scene. We call
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::548d53486465ce4befd548fbb52a5b4c
https://doi.org/10.1007/s00138-014-0633-2
https://doi.org/10.1007/s00138-014-0633-2
Publikováno v:
ICIP
This paper describes a method for calibrating non-overlapping cameras in a simple way: using markers on the cameras. By adding an AR (Augmented Reality) marker to a camera, we can find the transformation between the fixed AR marker and the camera's c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::defa6260b13aded2f3d5d709c0ceeb6f
https://doi.org/10.1109/icip.2016.7532544
https://doi.org/10.1109/icip.2016.7532544
Publikováno v:
ICIP
In this paper, we propose a method for detecting Scale-Invariant Point Feature(SIPF) including 3D keypoints Detector and feature descriptor. To detect SIPF, we first estimate a keyscale for point cloud, and calculate the covariance matrix of each 3D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d48f5aa7036d77132b40acc95130b7c0
https://doi.org/10.1109/icip.2015.7351275
https://doi.org/10.1109/icip.2015.7351275