CAP 4453 Robot Vision Home Page
Instructor: Dr. Niels da Vitoria Lobo
email: niels@cs.ucf.edu (put CAP4453 and your name in subject line)
Office Location: Virtual (answering emails)
Office Hours: Mon/Tue/Wed 11:45am -- 1pm
Office Phone: 407-823-2873 (407-UCF-CURE) but better to send email
TA's Office Hours: ????day 1pm and ????day 2pm
If student can't make TA's hours, call the main TA (???-???-???3,
??????????????, email: ???????????????@knights.ucf.edu;
secondarily call ???;
s/he will reply, and make arrangements to meet at a mutually convenient time.
How to do the assignments
Update 50:
Update 31: Nov 16 : Assignment Deep Learning MNIST (Required):
Update 30: Nov 2:
Update 29: Nov 2: Optical Flow Assignment (Required):
Here is the set of directions for installing OpenCV and doing the
Optical Flow demo.
4453OpticalFlowOpenCVImplem5.pdf
In this assignment, you will run the Optical Flow algorithm from the
OpenCV Library. Follow the directions in the provided pdf notes (above) to
see how to install Visual Studio 2017, the OpenCV Library, and the
code that will call the appropriate modules from the library.
You are expected to show a live demo of your camera running the
optical flow (if this is impossible, you are allowed to run the
algorithm on two frames, as shown in the pdf directions). The Optical Flow
algorithm has been implemented in the library by following the theory that
is presented in the paper (bouguetopticalflow.pdf in Update 30).
These equations in the paper are similar to the ones discussed in
our Optical Flow notes (how to get results for 3 or more points), but
are derived in a different manner, and use a Pyramidal approach that is
also described in the paper. (You do not need to understand that paper to
obtain good experimental results).
For showing your working demo, you will do a live
demo with the grader, and will show that your cam is able to see a moving
pattern, such as some text on a sheet of paper (that is moved slowly),
and the cam window displays the optical flow vectors.
Update 28: Oct 15:
Update 27: Oct 12:
Required Assignment Two: In this assignment, you will download and run
our implementation of AdaBoost, using the positive and negative examples
we have provided.
Carefully read the steps in here,
4453AdaboostAssignFall20a.pdf
Unzip the zip file.
Everything ( vboost, vdetect, positive and scenery)
is included in the .zip file (positive and scenery are in ..\AdaBoost\vboost,
Germany.pgm is in ..\AdaBoost).
Should you run into any issues while compiling the software, or during
running it, send an email to niels@cs.ucf.edu.
For judging whether you are on the right track to success with this assignment,
run the test on the German Soccer Team image. After all the improvements
(such as training on 2000 images of each class),
your results should be such that most of the faces are found, and there are few
False Positives (boxes drawn in places where there are no faces). There is
no partial credit for this Assignment, you must succeed fully to
get the points. For grading, you will meet the grader and show the program
running and getting the result on an image that we will provide you.
Update 26: Oct 11:
Practice Test TWO Question One and Project Preparation
questionOne.text
Update 25 Oct 8:
Convolutional Neural Net slides
4453NeuralNetworksConvolutional5.pptx
Update 24: Oct 6:
Intro Neural Net slides
4453NeuralNetworks4-1.pdf
Update 23: Oct 6 :
Optical Flow slides 4 :
4453opticFlowPpt4a.pptx
Update 22: Oct 1 :
Optical Flow slides 3 :
4453opticFlowPpt3.pptx
Update 21: Oct 1:
Some Linear Algebra slides:
4453LinAlg2.pptx
Update 20: Sep 29:
Optical Flow slides 2 :
4453opticFlowPpt22.pptx
Update 19: Sep 29:
Some Linear Algebra slides:
4453LinAlg1.pptx
Update 18: Sep 29:
Optical Flow slides 1 :
4453opticFlowPpt1new.pptx
Update 17: Sep 16:
This helps answer Q1 on Practice Test One
4453PracTestOneWrittenAnswersQ1v1.docx
Update 16: Sep 15:
Extra Slides for topic of AdaBoost
4453Extra1.jpg
4453Extra2.jpg
4453Extra3.jpg
Update 15: Sep 15:
Practice Test One
examOnePrac2.001.pdf
In addition to this list of questions, there will be a few (7 or 8) single-point
questions that will test if the student has understood deeper issues and details
about the study material. This practice test corresponds to about 85 percent of the actual test.
Update 14: Sep 10:
BoostingTWO slides:
4453FaceDetectionTWO_UsingAdaboost.pptx
Update 13: Sep 8:
For the face detection topic, Google: viola jones robust real-time object
Then, select the paper that is found at
www.cs.cmu.edu/~efros/courses/LBMV07/Papers (or www.cs.cmu.edu/courses/Papers) named viola-IJCV-01.pdf
Update 12: Sep 8:
Boosting slides:
4453FaceDetectionCusingAdaboost.pptx
Update 11: Sep 4 :
Zoom recording for the Lecture of September 3 is now viewable.
Please go to the
webcourses Announcements to get the youTube link.
Update 10: Sep 3 :
Update 9: Sep 1 :
Zoom recording for the Lecture of September 1 is now viewable.
Please go to the
webcourses page, and look at the Announcements to get the youTube link.
Update 8: Sep 1 :
The zoom link for today's lecture will be in the webcourses Announcements at 2:40pm, class
starts at 3pm, but you can start earlier if you have questions for me.
Update 7: Aug 28:
Zoom recording for the Lecture of August 27 is now viewable.
Please go to the
webcourses page, and look at the Announcements to get the youTube link.
Update 6: Aug 27:
Update 5: Aug 27:
Update 4: Aug 26:
Zoom recordings for the Lecture of August 25, these recordings are now viewable.
To get the 3 youTube links (for each of 3 parts), please go to the
webcourses page, and look at the Announcements (panel on the left).
Update 3: Aug 25:
Assignment 0:
Due to Federal Government rules
related to financial aid, you must go to
Webcourses and complete Assignment Zero before the end of
this coming Friday, Aug 28, 2020.
Update 2: Aug 25:
Update 1: Aug 25:
Class Syllabus
syllabus.pdf
Programs
Input Images
Output Images
Ignore
Intro To C