Schedule (CZ course)
Schedule (EN course)
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Computer Vision Methods Labs
Labs plan
Labs are organized in four main topics: Correspondence problem, Indexing and image retrieval, Object tracking, Convolutional neural networks. Each topic is covered by approximately two to four labs.
Zoom link for the remote labs (EuroTeQ project students) on Thursday 14:15 https://feectu.zoom.us/j/97922104602
Week | Date | Topic | Recording |
1 | 16.2. | Introduction to Image Processing in python using PyTorch. | recording |
2 | 23.2 | Convolutional Neural Networks: training a classifier | recording |
3 | 2.3. | Convolutional Neural Networks II: image colorization | recording |
4 | 9.3. | Correspondence problem I, detection of the interest points. | recording |
5 | 16.3. | Correspondence problem II, computing local invariant description. | recording |
6 | 23.3. | Correspondence problem III, finding tenative correspondences and RANSAC. | recording |
7 | 30.3. | Correspondence problem, summary. | There is no new task, see recording for 23.03.2002 |
8 | 6.4. | Image Retrieval I, image representation with set of visual words. TF-IDF weighting | |
9 | 13.4. | Image Retrieval II, fast spatial verification, query expansion. | |
10 | 20.4. | Image Retrieval III, complete pipeline for image retrieval in large databases. | |
11 | 27.4. | Extra time for working on previous assignment / No lab held in classroom | |
12 | 4.5. | Tracking I, Kanade-Lucas-Tomasi tracking (KLT tracker) | |
13 | 11.5. | Rector's day. Tracking II, KCF tracker discussed on the Monday (9.5.) lecture | |
14 | 18.5. | Finishing the assignments [update 18.5. : classroom lab cancelled due to illness of tutor] | |
Labs will be accompanied with a simple programming task. Detailed specification of the tasks is described in each of the labs. Students will upload their results and their codes through the
BRUTE system.
Each lab will usually consists of three parts:
Discussion on the last lecture. Students will be free to ask any questions related to the last lecture. At the end of this session, a teacher will pose a question to a volunteer/random student. If the student answers correctly, he/she will get a single bonus point.
Working on the current task. Students are free to ask any specific questions, discuss their current results, resolve any programming issues.
Short introduction of the next task. The teacher will briefly introduce the next problem, give some hints and answer possible questions.
Assessment
You are obliged to carry out all programming tasks at least a minimal required quality. All tasks must be carried out individually! You are free to discuss the problems with your colleagues, however the code must be written strictly by yourself. See plagiarism if you are unsure what is allowed.
Evaluation Policy
The grading points from the labs will contribute to 50 percent of your course evaluation. It is required to obtain at least half of the points for each programming task.
Each task uploaded after the due date is penalized as follows:
0.015pts for every hour after the deadline (= 2.5pts/7days)
The maximum penalty is 60% of the maximum points, e.g. for the task uploaded in 1 month late, you will get < =40%.
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