Object Tracking on a Monopoly Game Board

Object Tracking on a Monopoly Game Board

Author: Nathan Hoebeke

Supervisors: Maxim Van de Wynckel, Prof. Dr. Beat Signer

About

The goal of this dataset was to track game pieces on the physical game board of Monopoly. We make use of object classification where our training data consists of 100 pictures (taken at an angle) of the game board in order to classify the individual (moving) pieces. The training dataset was on the 9th of April 2023 and the test date recorded on the 7th of May 2023 using an iPhone 13 mini and iPhone 12.

Two participants played a game of Monopoly and each individually took pictures of the current game state after every move. These images were then processed by our application to determine the location of pawns and other game pieces such as the red and green houses.

Raw images are unprocessed but may have minor edits to ensure anonymisation of participants in the background. We used Roboflow to label and train our dataset which is included in this repository.

For more information about our processing and this dataset you can download the full Bachelor thesis here: https://wise.vub.ac.be/thesis/location-tracking-physical-game-board (download link available after embargo at the end of the academic year)

This dataset was published as part of the bachelor thesis: Location Tracking on a Physical Game Board for obtaining the degree of Bachelor in Computer Sciences at the Vrije Universiteit Brussel.

Data

Dataset contents

• model: Trained YOLOv5 model with labels. This dataset can also be found here.
• train: Training data made by the author.
  • raw: Raw pictures of the game board at various states.
    • GAME_2023-04-09_<HH>-<MM>-<SS>.jpg: Images formatted based on the date and time when they were captured.
  • processed: Processed pictures with perspective transformation applied.
    • canvas<X>.png: (Pre)-processed image.
• test: Test data made by indepedent participants.
  • participant_1: Participant 1 data
    • raw: Raw pictures of the game board taken by the parcipant after every move.
      • GAME_2023-05-07_<HH>-<MM>-<SS>.jpg: Images formatted based on the date and time when they were captured.
    • processed: Processed pictures with perspective transformation applied. Yellow rectangles are included when our own algorithm was able to determine the location.
      • canvas<X>.png: Processed image.
  • participant_2: Participant 2 data
    • raw: Raw pictures of the game board taken by the parcipant after every move.
      • GAME_2023-05-07_<HH>-<MM>-<SS>.jpg: Images formatted based on the date and time when they were captured.
• README.md: Documentation and information about the dataset.

License

This license applies to the dataset for the game Monopoly. Any artwork or intellectual property from the game that is captured by this dataset is property of Hasbro, Inc.

Copyright 2022-2023 Nathan Hoebeke, Beat Signer, Maxim Van de Wynckel, Vrije Universiteit Brussel

Permission is hereby granted, free of charge, to any person obtaining a copy of this dataset and associated documentation files (the “Dataset”), to deal in the Dataset without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Dataset, and to permit persons to whom the Dataset is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions that make use of the Dataset.

THE DATASET IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATASET OR THE USE OR OTHER DEALINGS IN THE DATASET.