2015 IEEE International Conference on Robotics and Automation (ICRA) 2015
DOI: 10.1109/icra.2015.7139870
|View full text |Cite
|
Sign up to set email alerts
|

Camera calibration correction in Shape from Inconsistent Silhouette

Abstract: The use of shape from silhouette for reconstruction tasks is plagued by two types of realworld errors: camera calibration error and silhouette segmentation error. When either error is present, we call the problem the Shape from Inconsistent Silhouette (SfIS) problem. In this paper, we show how small camera calibration error can be corrected when using a previously-published SfIS technique to generate a reconstruction, by using an Iterative Closest Point (ICP) approach. We give formulations under two scenarios:… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
1

Relationship

1
0

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 27 publications
(40 reference statements)
0
1
0
Order By: Relevance
“…The 3D Tree Reconstruction and Shape Analyses. A representative WEEP tree was analyzed by using an in-house-designed structural phenotyping system at the US Department of Agriculture, Agricultural Research Service Appalachian Fruit Research Station, Kearneysville, WV (72)(73)(74)(75). Briefly, the tree was imaged against a blue background via a robotic arm with two digital cameras mounted on the robot's end effector.…”
Section: Methodsmentioning
confidence: 99%
“…The 3D Tree Reconstruction and Shape Analyses. A representative WEEP tree was analyzed by using an in-house-designed structural phenotyping system at the US Department of Agriculture, Agricultural Research Service Appalachian Fruit Research Station, Kearneysville, WV (72)(73)(74)(75). Briefly, the tree was imaged against a blue background via a robotic arm with two digital cameras mounted on the robot's end effector.…”
Section: Methodsmentioning
confidence: 99%