Photogrammetry I - 16a - DLT & Camera Calibration (2015)

[@KitkatTrading2024]

Very efficient way of summarizing a complex process. Thank you!

[@diana-valeriavacaru1673]

Finally a presentation that answered so many of my questions ^^

[@saptamighosh106]

Thank you professor for clarifying the mathematics behind the camera calibration.

[@williamburton4173]

Very intuitive walk-through of the derivation, thank you!

[@ArdianUmam]

Many thanks for the intuitive and clear lecture...

[@zzz123zzz13245]

in 30:38 it should be vi_transpose*vj (the inner product which gives you a number) and not vi*vj_transpose (the outer product which will give you a matrix).

[@张快快快]

I agree

[@KitkatTrading2024]

If I have a lot of points (>>6), would that help improve the calibration accuracy?

[@malharjajoo7393]

Absolutely fantastic.
Great summary at 46:46

[@CyrillStachniss]

Thanks!

[@pedrorodriguez1798]

Does anybody know where to find a numerical example with this computation? would be really helpful. Also I think it is possible to use vanighing points to compute P, but I can't find examples.

[@julianestebanherrerabenavi989]

Thank you very much for your explanation. It was very useful for me.

[@zengzhaocheng]

38:28 Since we just know the matrix P, how do we solve the Xo with unknown K and R? Thanks in advance.
update:Is that just by picking out the first 3 column as H_infinity and last column as h?

[@williambonvini5806]

Awesome explanation, well done!

[@rabiafyz9952]

Thanks for good explanation.
I am working on self camera calibration. and your lectures helped me to revise what i know about self calibration. And thanks for giving information about decomposition of projection matrix P. I was really wandering how can i get intrinsic and extrinsic parameters from projection matrix p.
My main problem or i am stuck or confuse at solving the self calibration equations.
Also now i will look at QR decomposition techniques. Thanks again. :)

[@rabiafyz9952]

Please make a lecture on self camera calibration if possible. thanks .

[@rstim]

Thanks Cyrill, these videos have really helped me out.
I do however have one question, you say that 'next week' you discuss spacial resection (or projective 3-point-algorithm) which I am really interested in, but I am unable to find the video of it on your channel.
Would be great if you could help out!

[@gunagopi007]

It's been recently uploaded here. ua-cam.com/video/N1aCvzFll6Q/v-deo.html

[@udaradarshanapanamullaarac3330]

In slide number 41 you said not to locate all points on a plane so that can turn all z point to zero. so can we get over from that, if we put all the points on the same plane and add the same value to Z (ex: Z= 1)?
And thanks for this great step by step explanation~~

[@tanyashukla8206]

Excellent explanation :) helped a lot !

[@balamuruganthambiraja4498]

Hi Cyril,
Can you please explain the relation why we need atleast 3 points for 6 unknowns and 6 points for 11 unknowns ?
Thanks.

[@CyrillStachniss]

Each point provides 2 observations (x and y) and you need to relate that with the DoF to estimate.

[@balamuruganthambiraja4498]

Thanks Cyrill...

[@NamVeteran420]

thank you for this. excellent series

[@xiaotongding3035]

Thank you very much! This video is very helpful!

[@milingzhang6181]

Thank you sir from China.

[@gadget_unbox]

Thanks a lot for a very good explanation :)

[@abhishektyagi154]

Thank you

[@linghanqian4148]

Thanks, helps a lot:)

[@liuweiwei1886]

thx a lot , really appreciate it