I applied this to the Rubik's Cube for stock market charts. The results can change the world.

Kalman + locally weighted scatterplot smoothing.

Please Make a Pathway to learn Robotics Is it okay to learn SLAM then Mobile Sensing then Motion Planning Or what should be learned before the other?

Brilliant!

6:07 Intro to PhotoGrammetry .

Amazing explanation, still providing value after all these years

Great lecture! Is it possible to get the slides as a pdf file?

I came across your slides on the introduction to neural networks, and I have to say, they were far more helpful than the ones provided by my university. I can’t express how grateful I am for your clear and concise explanations. I even searched online to find more of your slides but couldn’t locate them. Your videos are incredibly helpful

for data association, we only use the ICP? do we ever consider graph based data association methods? how they fit into your framework?

Excellent lecture! Thank you and team very much for sharing your wisdom and your hard work!

Thank you man

Vielleicht sollte man auch mal erwähnen, dass Denkmalschutz nur mit einer rekonstruierbaren Zentralperspektive möglich ist, was ein Smartphone nicht kann, weil es nicht geometrisch abbildet - da nützen die Anzahl der PIXEL rein gar nichts. Smartphonebilder werden immer nur ein "riesen Bildlappen" abbilden.

Nice work! I am wondering isnt it a bit much to use 5 cameras to make 3D model while you have the arm that can move in several directions? (and all the other attached cameras on the vehicle frame, looks a lot of data) For a small region, as a proof of concept, maybe its nice but I think it would be better to reduce hardware and data preprocessing costs in long term

Pretty sure your cameras don't need to be that expensive.

Great job sir

I would like this professor to visit cameroon.

Go Pheno-Inspect!

Thank you so much for this wonderful C++ course! Very clearly explained and very helpful!

Don't

Very nice lecture! Thank you and team very much for sharing your wisdom!

Very clear and helpful! Thank you very much, Igor!

Thank you very much for sharing this lecture - it was a nice, brief introduction to the topic!

A good lecture! Thank you for sharing!

thank you so much, love your videos

Thank you and team very much for sharing your wisdom freely to public!

Thank you very much, Vizzo! Nice lectures!

is this course up to date and informative after 11 years?

Thanks for the lecture!

Thanks for sharing this lecture! : )

Doesn't the function "swap" do the same stuff but faster? Minute 11.00 (idk if swap works also with objects)

Thank you for sharing the course. : )

Thank you so much for this lecture, Vizzo, Cyrill and team! Excellent teaching and sharing!

Thank you so much! Excellent and so funny too! I am laughing through the lecture! Haha~~

Excellent lecture! Thank you for sharing!

Okey, and how to do reverse?

Dear Cyril , thank you so much for your nice explanation.

in the returning local variable reference example, printing a message can make thing work experience actually happened to me some years ago. As I could not find out the actual cause of it, I have to leave that meaningless debug message overthere. I even suspected that there maybe was a bug in the compiler. Now I know the reason, thanks :D

This is the best, most straightforward, simplest explanation lecture I can have. Thank you so much for the lecture.

Thank you! it was very helpful

I've searched and searched for a clear, intuitive explanation of the camera imaging model. My search ends here!

I used it on my MSC work in 2013. Thanks for the contribution

Great video, thank you!

How is downsampling handled for cases when the number of detections provided per scan is less than N ?

Great video

thank u sir

un argentino, grande

Great video!

This lecture has been around for six years, but it remains the best. As I gain more practical experience, I realize just how many important messages this lecture conveys.

excellent

great works!