COMP52615 Computer Vision Assignment: Detection of a badminton court and then players on the court
Module COMP52615
Assignment
MISCADA Computer Vision module academic year 2023/2024
Introduction
In this assignment, you are asked to implement software for the detection of a badminton court and then players on the court. You are then asked to track the players on the court. Data are provided, read the instructions on how to get hold of the dataset in the dedicated section. Image frames of a video clip of two international badminton matches have been zipped.
Task specification
A badminton court is defined by a rectangular area delimited by lines. The court in the available dataset is green, although a court could be of different colour. A badminton court has a rectangular shape of some given dimensions (see figure 1 for more details), divided into rectangular regions, related to the game itself.
figure 1: A badminton court, left for single, right for double matches.
You might be a badminton player, perhaps a professional, however, if you are not familiar with
the game, you can find the international rules at https://olympics.com/en/news/badminton-
guide-how-to-play-rules-olympic-history.
We will work with both single and double matches. You are asked to implement solutions to
solve the following tasks:
• Task 1: Image frames detection - for this part of the assignment, you are asked to utilise both colour segmentation and pattern segmentation to extract all the frames in the provided video clips that contain the full badminton court. A court is fully visible when an
Module COMP52615
action is shot from the distance, to provide full visibility of a game; this could be from the side of a court, or from behind one of the two teams. See figure 2 for examples. Expected Output: Image frames with a fully visible court should be saved in a list of image names, easily accessible to retrieve the frames for further processing; please do adhere to the image frame names of the provided datasets.
figure 2: left, single match, from perspective of the player in black right, a double match, from the perspective of the yellow team.
• Task 2: Court detection - for all the extracted image frames that contain the full view of
the court, you are asked to annotate the court with lines. For this, you will have to develop
code that extracts the lines and effectively builds a 2D model of the court.
Expected Output: both coordinates of the polygons used to highlight the court image
frames with overlapped court should be provided.
• Task 3: Player detection - for this part, you are asked to exploit one of the taught
algorithms to extract bounding boxes that identify the players on the court. If a person is
detected outside the court, its bounding box must be discarded as an outlier.
Expected Output: both coordinates of the rectangles bounding the players and the image
frames with overlapped bounding rectangles should be provided.
• Task 4: Player tracking - for this part, you are asked to use one of the taught techniques to track the players. To be borne in mind, while the TV camera does not move much from the best perspective of the game, it might still pan a little, this movement will have to be compensated for by using the information about the court.
Expected Output: For this task you should provide short video clips using the image frames and overlapped court lines and bounding rectangles for the players.
Dataset
They are two zip files containing image frames of short clips of two badminton matches, a single and a double, both played at international level. For simplicity, image frames from clips have been extracted and compressed in zip files.
