dbo:abstract
|
- Chessboards arise frequently in computer vision theory and practice because their highly structured geometry is well-suited for algorithmic detection and processing. The appearance of chessboards in computer vision can be divided into two main areas: camera calibration and feature extraction. This article provides a unified discussion of the role that chessboards play in the canonical methods from these two areas, including references to the seminal literature, examples, and pointers to software implementations. (en)
|
dbo:thumbnail
| |
dbo:wikiPageExternalLink
| |
dbo:wikiPageID
| |
dbo:wikiPageLength
|
- 16273 (xsd:nonNegativeInteger)
|
dbo:wikiPageRevisionID
| |
dbo:wikiPageWikiLink
| |
dbp:align
| |
dbp:caption
|
- 3 (xsd:integer)
- (en)
- Canny edge detector applied to chessboard image (en)
- Output of Harris corner detector (en)
- Perspective-transformed chessboard image (en)
- Reconstructed orientations (en)
- Hough transform of edge image with 19 largest local maxima denoted (en)
- Lines parameterized by Hough transform local maxima (en)
- Multiple views of a chessboard for multiplane calibration (en)
|
dbp:height
|
- 384 (xsd:integer)
- 471 (xsd:integer)
- 548 (xsd:integer)
- 678 (xsd:integer)
- 728 (xsd:integer)
|
dbp:image
|
- Chessboard calibration setup.png (en)
- Harris corners detected on chessboard.png (en)
- Multiple chessboard views.png (en)
- Perspective chessboard detected lines.png (en)
- Perspective chessboard edges.png (en)
- Perspective chessboard hough transform.png (en)
- Perspective chessboard.png (en)
- Reconstructed boards camera.png (en)
- Reconstructed boards world.png (en)
|
dbp:textAlign
| |
dbp:title
|
- Example: calibration rig (en)
- Example: corner detection (en)
- Example: line detection (en)
- Example: multiplane calibration (en)
|
dbp:totalWidth
|
- 300 (xsd:integer)
- 600 (xsd:integer)
- 900 (xsd:integer)
- 1000 (xsd:integer)
|
dbp:width
|
- 507 (xsd:integer)
- 529 (xsd:integer)
- 681 (xsd:integer)
- 767 (xsd:integer)
- 1128 (xsd:integer)
|
dbp:wikiPageUsesTemplate
| |
dcterms:subject
| |
rdfs:comment
|
- Chessboards arise frequently in computer vision theory and practice because their highly structured geometry is well-suited for algorithmic detection and processing. The appearance of chessboards in computer vision can be divided into two main areas: camera calibration and feature extraction. This article provides a unified discussion of the role that chessboards play in the canonical methods from these two areas, including references to the seminal literature, examples, and pointers to software implementations. (en)
|
rdfs:label
|
- Chessboard detection (en)
|
owl:sameAs
| |
prov:wasDerivedFrom
| |
foaf:depiction
| |
foaf:isPrimaryTopicOf
| |
is dbo:wikiPageRedirects
of | |
is dbo:wikiPageWikiLink
of | |
is foaf:primaryTopic
of | |