ksimek.github.io

Sightations ← Kyle Simek

Larr; A Computer Vision Blog. Q and A: Recovering pose of a calibrated camera - Algebraic vs. Geometric method? March 29, 2015. This week I received an email with a question about recovering camera pose:. Q: I have images with a known intrinsic matrix, and corresponding points in world and image coordinates. What's the best technique to resolve the extrinsic matrix? Hartley and Zisserman cover geometric and algebraic approaches. What are the tradeoffs between the geometric and algebraic approaches? Exami...

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Sightations ← Kyle Simek | ksimek.github.io Reviews

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Larr; A Computer Vision Blog. Q and A: Recovering pose of a calibrated camera - Algebraic vs. Geometric method? March 29, 2015. This week I received an email with a question about recovering camera pose:. Q: I have images with a known intrinsic matrix, and corresponding points in world and image coordinates. What's the best technique to resolve the extrinsic matrix? Hartley and Zisserman cover geometric and algebraic approaches. What are the tradeoffs between the geometric and algebraic approaches? Exami...

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3 archive

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7 glfrustum

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Sightations ← Kyle Simek | ksimek.github.io Reviews

https://ksimek.github.io

Larr; A Computer Vision Blog. Q and A: Recovering pose of a calibrated camera - Algebraic vs. Geometric method? March 29, 2015. This week I received an email with a question about recovering camera pose:. Q: I have images with a known intrinsic matrix, and corresponding points in world and image coordinates. What's the best technique to resolve the extrinsic matrix? Hartley and Zisserman cover geometric and algebraic approaches. What are the tradeoffs between the geometric and algebraic approaches? Exami...

INTERNAL PAGES

ksimek.github.io

1

Dissecting the Camera Matrix, Part 1: Extrinsic/Intrinsic Decomposition ←

http://ksimek.github.io/2012/08/14/decompose

Larr; A Computer Vision Blog. Dissecting the Camera Matrix, Part 1: Extrinsic/Intrinsic Decomposition. August 14, 2012. Edited June 2, 2013 - Fixed "step 3" and final equation. Not this kind of decomposition. So, you've been playing around a new computer vision library, and you've managed to calibrate your camera. now what do you do with it? It would be a lot more useful if you could get at the camera's position or find out it's field-of view. You crack open your trusty copy of Hartley and Zisserman.

2

Calibrated Cameras and gluPerspective ←

http://ksimek.github.io/2013/06/18/calibrated-cameras-and-gluperspective

Larr; A Computer Vision Blog. Calibrated Cameras and gluPerspective. June 18, 2013. After posting my last article relating glFrustum to the intrinsic camera matrix. I receieved some emails asking how the (now deprecated) gluPerspective. Function relates to the intrinsic matrix. We can show a similar result with. As we did with. Namely that it is the product of a. The matrix generated by. Begin{align} f &= cot(fovy/2) C' &= - frac{far near}{far - near} D' &= - frac{2 ; far ; near}{far - near} end{align} ].

3

Dissecting the Camera Matrix, Part 2: The Extrinsic Matrix ←

http://ksimek.github.io/2012/08/22/extrinsic

Larr; A Computer Vision Blog. Dissecting the Camera Matrix, Part 2: The Extrinsic Matrix. August 22, 2012. Welcome to the third post in the series " The Perspecive Camera - An Interactive Tour. In the last post, we learned how to decompose the camera matrix. The Extrinsic Camera Matrix. And a translation vector. The extrinsic matrix takes the form of a rigid transformation matrix: a 3x3 rotation matrix in the left-block, and 3x1 translation column-vector in the right:. It's common to see a version of thi...

4

Compiling ELSD (Ellipse and Line Segment Detector) on OS X ←

http://ksimek.github.io/2014/04/28/compiling-elsd-on-osx

Larr; A Computer Vision Blog. Compiling ELSD (Ellipse and Line Segment Detector) on OS X. April 28, 2014. ELSD is a new program. For detecting line segments and elliptical curves in images. It gives very impressive results. By using a novel model selection criterion to distinguish noise curves from foreground, as detailed in the author's ECCV 2012 paper. Most impressive, it works out of the box with no parameter tuning. The authors have generously released their code under Affero GPL. Posted by Kyle Simek.

5

Calibrated Cameras in OpenGL without glFrustum ←

http://ksimek.github.io/2013/06/03/calibrated_cameras_in_opengl

Larr; A Computer Vision Blog. Calibrated Cameras in OpenGL without glFrustum. June 03, 2013. Author's note: some of this content appeared on my old blog as " Simulating Calibrated Cameras in OpenGL. Which contained some errors and missing equations and suffered from general badness. I hope you'll find this version to be less terrible. June 18, 2013): added negative signs to definitions of C' and D'. August 19, 2013): James Gregson has posted an implementation in C. You can. And you don't have to jett...

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Larr; A Computer Vision Blog. Q and A: Recovering pose of a calibrated camera - Algebraic vs. Geometric method? March 29, 2015. This week I received an email with a question about recovering camera pose:. Q: I have images with a known intrinsic matrix, and corresponding points in world and image coordinates. What's the best technique to resolve the extrinsic matrix? Hartley and Zisserman cover geometric and algebraic approaches. What are the tradeoffs between the geometric and algebraic approaches? Exami...

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