Learner Reviews & Feedback for Robotics: Perception by University of Pennsylvania

Excellent Course, at the beginning I was a beginner in this topic and now I learned a lot about computer vision and visual perception. That is a fundamental part of mobil robot localization and planning. As a feedback, I only recomend more numerical examples, this would help to understand more quickly the topics.

This is an excellent courses for beginners and for experienced engineers interested in learning the basics of Bundle Adjustment and 3D geometry. The ideas are very well explained and the exercises in Matlab contribute to understanding the concepts taught. I could not recommend this course more highly.

This course is a tough one, the assignments are challenging. One problem with teh course is the use of english subtitles, there some errors on mathematical terms that makes more difficult to understand what is being explained (and sometimes the teachers' english is not very clear).

Course is unusually difficult compared to the others in the series. You'll learn plenty of stuff, though, which is useful not just in robotics itself but many other applications with a mobile camera (such as stitching panoramas taken with your phone, or producing CGI).

Interesting material, presented well, very on-top and supportive TAs. I wish the second assignment had been the first assignment (the current first assignment is very basic and can be scrapped), so that the 4th assignment could be about implementing bundle adjustment.

It is a great course and the material is really good. I understand creating an automatic grader is never easy, but in estimation problems if we do things certain way it will lead to differences, but not necessarily bad results. Wish this could have an easier way :).

I was looking for a good course on Computer Vision which tells about its basics, Epipolar Geometry, SFM, etc. and found this module under the Robotics course. The course content was really good and explanatory. Thank You,

Amit Kumar

Extremely challenging... took me 3 months to pass the course. It required me to go to Khan Academy and revise all about Linear Algebra + Derivatives... Especially Null Space and Jacobian ... It's challenging but it's really good.

use the forums, and re-watch videos with the quiz pulled up

good derivations / walkthrough of spatial concepts behind the math used in various processing done in perception like SFM, working with monocular RGB data

Good intro course for someone has no prior knowledge in Computer Vision. The entire course is about linear algebra practices. Professors provide lots of information, assignment projects are interesting.

This course was truly amazing. It was challenging and I learned a lot of cool stuff. It would have been better if more animations were included in explaining complex concepts and equations.

Outstanding Course! I could always count on Prof.Jianbo to crunch some of the most complex and confusing parts of the course into a much easier understandable language.

Great course for those who wants to understand how classical SLAM systems work. I think it would be a bit more practical if the assignments were made in python.

Course is nicely organized and helps even a novice without much in depth knowledge of image processing to understand the concepts

Awesome material! I think this is the one course of the specialization that had the appropriate amount of work for the timeline.

It is hard course, thoroughly enjoyed it. Lessons on how to effectively use vanishing points was very useful.

Great lectures! I felt a little confused at the beginning , but everything makes sense by the end of class.

One of the most usefful courses I have taken by the coursera. Thank you for useful materail covered here.

Solid Material as an introductory course and gives glimpse on the new horizons on computer vision.

The professors have very detailed description, and the programming assignments are valuable.

Very good. Teachers worked hard. Practical and quite comprehensive for such short term.

This was by far the best course. Very difficult and complex. But it is worth studying

Great course, I been able to develop new skills and knowledge. Highly Recommended.

Really good course for getting a sound foundation on geometry of computer vision.

Excellent course, very nice field of research with a lot of space for innovation.