9. Constraints: Visual Object Recognition

hahah, yeah, the power of storytelling :D not the power of love or power of dream :D is the real power! the other two are fake power, just for propaganda.

Where is lecture 8 ? Or is it mistakenly labeled ?

Thank you for this great lecture.

this great man is worthy of being cloned ,,,your lectures are exquisited thanks mr, PATRICK WINSTON,,Colombia resiste may 2021

Eye enjoy this very much. :-)

RIP.

Somebody get this man some oxygen!

R.I.P Patrick Winston

what softwares do professor winston use for the demonstrations?

"It's still not solved." Why am I wasting my time watching this then? Maybe I should just go back to actually solving it and shit.

Boom! Tetris for Jeff!

Wish the professor could expand the binary mask technique (for finding correlation) to higher dimensions and to non-binary cases.

thank you for sharing.

I am just a B Tech first year student.... just a small query.... if we have orthographic projections... we take views from mutually perpendicular directions... if my coordinate system is set with axis parallel to our viewing direction then won't the computation be much easier.... view along x axis and view along y axis will always have same z coordinate and that along x and Z would have same y coordinate... so won't these condition actually give the object in 3d(I mean a 3 dimensional array with known XYZ coordinate of all vertices)... later then we can rotate and check if we can generate similar 2d images from 3d view?)....

very interesting, now back to my RPi3 and opencv AI logic. thanks.