College application research evidence · understanding and original contribution · Seoul and online
Project courseThe student keeps the work and the record they made.
Open Football Video: Rebuild Player, Number, and Position Data
Grades 9-12: rebuilding match data from video, jersey...
- Free consultation and level check
- Apgujeong classroom or online
- One-to-one or small group
- Registered academy no. 11882
Is Open Football Video: Rebuild Player, Number, and Position Data a good fit for high school students in Grades 9-12?
Open Football Video: Rebuild Player, Number, and Position Data is a good fit for students in grades 9-12 who are interested in rebuilding match data from video and jersey number recognition. CIT offers online or in-person lessons in Apgujeong, Gangnam, Seoul, in one-to-one or small-group formats. Students make a reproduced baseline with run logs, a before-and-after evaluation table, and a comparison web demo with a report or poster.
Students first reproduce the official SoccerNet game state reconstruction baseline, which recovers each player's team, role, jersey number, and pitch position from match video, on one validation clip. They trace where errors begin, choose one module such as team classification, jersey number reading, re-identification, or camera calibration, change a single setting, and compare before and after on the same clips and metric. Data and model files stay out of GitHub, and the work ends in a web demo showing both improved and worsened scenes, plus a research report or poster. The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits.
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I appreciated that a simple early idea was extended into an 'AI debate tool'. My child has always been interested in debate and social issues, so seeing that interest connect to the project makes me expect a more complete and distinctive result.
- Age group
- Grades 9-12
- Academic subject
- AI & Data, Arts, Media & Design, Research & PortfolioBrowse subject
- Course type
- Course
- Format
- Online or Apgujeong in person · one-to-one or small group
- Teaching language
- Korean by default, with complete English materials
- Curriculum status
- Lesson-readyEvery learning item includes the evidence, worked example, practical work, and tutor guidance required by CIT's lesson-ready standard.
From open research to student-owned work
Students inspect a relevant public source, reproduce the idea, then add an original question, feature, or test. Every source is public, and each lesson names the exact page it opens.
How can I explain this course to my child?
If questions about rebuilding match data from video or jersey number recognition keep making you ask why, Open Football Video: Rebuild Player, Number, and Position Data lets you investigate the question with evidence, then build and defend an extension of your own.
Which interests suggest this course?
- rebuilding match data from video
- jersey number recognition
- fair one-change experiments
What does the student finish?A reproduced baseline with run logs, a before-and-after evaluation table, and a comparison web demo with a report or poster.
Is this a good fit?
A strong fit for students who want to understand, build, test, or responsibly use AI systems.
Course placement follows current subject and coding readiness.
Students should be ready to document sources, methods, and limits.
Advanced tools are introduced after a clear baseline.
What will my child learn?
- Record Python, PyTorch, and CUDA versions and commits so the same results can be produced again.
- Trace back from the first wrong frame to find the module where an error starts.
- Fix the comparison clips and main metric before any change, then change a single setting and rerun.
- Compare improved scenes, worsened scenes, and processing time side by side, and write conclusions with limits.
How does the course progress?
- 1Reproducing the Official Baseline
Pin the environment and data, run the official baseline unchanged on one validation clip, and archive the results.
- 2Choosing One Research Problem
Rank errors by frequency, measurability, and run time, pick one research question, and split development and comparison scenes.
- 3Module Options
Study one module: teams, roles, jersey numbers, re-identification, tracking, camera calibration, or minimap position.
- 4One Change, Comparison, and Research Demo
Record the changed setting and finish a web demo of improved and worsened scenes plus a report or poster.
What counts as useful evidence?
A reproduced baseline with run logs, a before-and-after evaluation table, and a comparison web demo with a report or poster.
What should an admissions reader be able to see?
The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits.
Useful evidence may include a documented dataset, baseline comparison, model evaluation, error analysis, and a clear record of the student's own decisions.
The evidence an application reads is what the student understood, completed, and can explain.
The real research project this course reads
- SoccerNet/sn-gamestate
- pinned commit
1c9583450672 - licence GPL-3.0
- text files 113
The student removes one module from a public match-video pipeline and finds which stage was holding the result up. In class the project is separated into five boxes (input, memory, process, output, control). The lesson opens one of them, changes one value, and leaves the rest closed.
- InputWhat comes in?
The video frames, and the configuration file that says which modules to use
- MemoryWhat persists?
The run of boxes joined as one person: a single player's tracklet
- ProcessWhat transforms?
The stages that find players, read jersey numbers, split teams, and move screen coordinates onto the pitch
- OutputWhat leaves, and who uses it?
Player states drawn on the pitch, and the score against the reference answer
- Controlopened hereWhat decides when anything runs?
The configuration that decides which module is plugged in where, and the code that finds it
The files the lesson opens, by name. The course is not a walk through the repository; it opens a chosen few and says which.
One value moves and everything else stays. The right-hand column is the prediction written before the run, not a result; the work is reconciling the two.
On a narrow screen, swipe the picture sideways.
The universities and labs named here made the open projects this course reads. CIT designed the course independently; it is not an official, affiliated, or endorsed course.
Which sources were reviewed?
Catalog reviewed: 2026-09-30
Questions parents search before choosing this course
Is Open Football Video: Rebuild Player, Number, and Position Data a good fit for high school students in Grades 9-12?
Open Football Video: Rebuild Player, Number, and Position Data is a good fit for students in grades 9-12 who are interested in rebuilding match data from video and jersey number recognition. CIT offers online or in-person lessons in Apgujeong, Gangnam, Seoul, in one-to-one or small-group formats. Students make a reproduced baseline with run logs, a before-and-after evaluation table, and a comparison web demo with a report or poster.
Can my child take Open Football Video: Rebuild Player, Number, and Position Data online or in person, one-to-one or in a small group?
Yes. CIT offers online and in-person lessons at its Apgujeong academy in Gangnam, Seoul, with one-to-one and small-group options. A readiness consultation confirms the available format and starting point for the course.
Does my child need prior subject knowledge or coding experience for Open Football Video: Rebuild Player, Number, and Position Data?
Course placement follows current subject and coding readiness. Students should be ready to document sources, methods, and limits. Advanced tools are introduced after a clear baseline.
What will my child make or practice in Open Football Video: Rebuild Player, Number, and Position Data?
The main evidence is a reproduced baseline with run logs, a before-and-after evaluation table, and a comparison web demo with a report or poster. Students also document decisions, tests, feedback, and limits in age-appropriate language.
How can a student describe work from Open Football Video: Rebuild Player, Number, and Position Data in a college application?
The student sets their own question, then designs and tests a feature, model, interface, or solution of their own. In an application or interview, the student separates the material they drew on from their own decisions, results, failed attempts, revisions, and limits. Useful evidence may include a documented dataset, baseline comparison, model evaluation, error analysis, and a clear record of the student's own decisions.
How are the schedule and tuition for Open Football Video: Rebuild Player, Number, and Position Data determined?
CIT confirms the student's readiness, goal, location, class size, and current availability before recommending a course plan. The consultation and level check are free; tuition is explained before enrollment.
When should a student start?
There is no fixed intake month. CIT reviews the student's current school term, readiness, and available hours, then names the point in the course where they should begin.
The teachers are always attentive and considerate, so we feel comfortable trusting them with our child.
Where else parents check CIT
Choose the course after a readiness check
CIT can compare this course with nearby options by age, subject, and current preparation.