Semester.ly

Johns Hopkins University | EN.600.461

Computer Vision

3.0

credits

Average Course Rating

(3.82)

This course gives an overview of fundamental methods in computer vision from a computational perspective. Methods studied include: camera systems and their modelling, computation of 3-D geometry from binocular stereo, motion, and photometric stereo; and object recognition. Edge detection and color perception are covered as well. Elements of machine vision and biological vision are also included. Students may receive credit for at most one of EN.600.361 or EN.600.461 or EN.600.661. [Applications] Prerequisites (soft): intro programming, linear algebra, and prob/stat.

Fall 2012

(3.53)

Fall 2013

(4.14)

Fall 2014

(3.8)

Fall 2012

Professor: Gregory Hager

(3.53)

Students liked the interesting subject matter and the programming assignments. They also said the professor was a good teacher. However, many said that the course was disorganized and that the assignments were not clear. Students suggested having additional smaller projects instead of a few large assignments, as well as better lectures and lecture notes. Students should know that this is a chal enging course and they wil need to take time to study outside of class.

Fall 2013

Professor: Rene Vidal

(4.14)

Students thought that the best aspect of this course included the professor’s treatment of the material and the interesting information presented. Students found that the homework assignments to be time consuming but thorough in reinforcing the information taught in class. They did have some complaints about how the homework was graded, and found that code that worked on their computers did not work for the professor or TA. They suggested finding ways to shorten the homework or give students more time to complete the assignment, and to have TAs take longer to grade the work and get it working. Prospective students should know that although the course is time consuming, they wil learn a tremendous amount. They need to have a background in programming, linear algebra, and optimization to get the most out of this class.

Fall 2014

Professor: Rene Vidal

(3.8)

Students thought the best aspect of this class was the interesting course material that was taught by a knowledgeable instructor. They thought biggest drawback of the course was that the material covered in lectures was not always useful to completing assignments. Some students also felt that the mathematical aspects of the class could have been explained more effectively. Students believed that the course could have been improved with a clearer grading scheme and tests that more effectively tested their ability to use rather than just recite the concepts they learned. They thought it was most valuable for students considering taking this course to know that some knowledge of linear algebra was important for success in the class.