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Computational Problem Solving (5cr)

Code: DT10115-3001

General information


Enrollment
29.04.2025 - 31.10.2025
Registration for the implementation has begun.
Timing
15.05.2025 - 15.12.2025
Implementation is running.
Number of ECTS credits allocated
1 - 5
Local portion
0 cr
Virtual portion
5 cr
Mode of delivery
Distance learning
Unit
Open UAS
Campus
Online
Teaching languages
English
Seats
5 - 30
Degree programmes
Degree Programme in Information and Communication Technology
Teachers
Radu Mariescu-Istodor
Teacher in charge
Radu Mariescu-Istodor
Scheduling groups
Avoimen opiskelijat (Size: 50 . Open UAS : 50.)
Tutkinto-opiskelijat (myös ristiinopiskelu) (Size: 0 . Open UAS : 0.)
Groups
TOP25_26
Other Complimentary Studies Group Semester 2025-2026
KAKS25
Karelia, Open UAS, All, Fall, 2025
Small groups
Open UAS Students
Degree students
Course
DT10115

Evaluation scale

Approved/Rejected

Objective

- Understand and apply mathematical and computational methods for reconstructing movement and drawings from video footage.
- Analyze camera perspectives, distortions, and projections to infer spatial relationships.
- Design, implement, and evaluate simulations and visual explainers.
- Apply optimization techniques such as local search and gradient descent.
- Implement the solution using a programming language (eg. JavaScript or Python).

Content

The course is structured around a single challenge: reconstructing a pen’s path from footage of its movement in front of colored balls. Through this, students will explore:
- Trilateration and geometric localization techniques.
- Perspective analysis and size scaling based on visual input.
- Camera modeling (pinhole camera, lens distortion).
- Map projections (Azimuthal equidistant, Lambert equal-area).
- Simulations and visual debugging (using JavaScript and Three.js).
- Optimization strategies: local search, gradient descent, and genetic algorithms.
- Neural network applications in spatial estimation.
- Signal and image processing techniques for segmentation and motion analysis.
- Problem decomposition and algorithm design for real-world-inspired scenarios.

Location and time

Online

Materials

Original course notes and explainers by the instructor
Szeliski, R. Computer Vision: Algorithms and Applications (optional)

Teaching methods

The course is organized in 2 phases.

Phase 1 - The Competition (16.5.2025 - 15.7.2025) - ENDED
In this phase, students implemented their own solutions and got feedback from the teacher. Students earned badges which translated to credit points.
Competition Link: https://youtu.be/bZ8uSzZv0ew
Discord (#decode-the-drawings channel): https://discord.com/invite/gJFcF5XVn9

Phase 2 - The Course (22.8.2025 - 15.12.2025) - ONGOING
Video Course: https://youtu.be/wH6gZB7m22k
The course asks for a number of 13 homework assignments to be completed. Students can choose which ones they want to solve (max 5, 1 assignment = 1 credit point).
When completed, or if you have any questions, contact your teacher on Discord via a private message or on the #decode-the-drawings public channel: https://discord.com/invite/gJFcF5XVn9

Assessment criteria, approved/failed

The course is passed by earning a single badge during the competition, or doing one single homework assignment during the course.
The number of badges / homework assignments increase the number of credits (max 5 credits).

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