The aim of this thesis is to examine the possibility of a court detection program for sports videos that can identify the court even when some important elements are not visible. The study will also analyze what external factors may impact the program's accuracy in detecting all relevant elements. These questions are answered through a combination of computer vision techniques and algorithms. The study utilizes Design Science Research (DSR) as its research methodology to develop an artifact. A dataset of padel sports videos are evaluated to measure the artifacts accuracy. The artifact utilizes multiple computer vision techniques from the OpenCV library to detect relevant lines and edges and project them onto the frame using a predetermined court model as reference. The findings indicated that the developed artifact demonstrated a relatively consistent level of accuracy in court detection across multiple courts, whenever a detection was made. However, the frequency of successful detections exhibited some inconsistency. The research also found that external factors did not significantly influence the accuracy of court detection, yet they posed challenges to the program's overall consistency.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-61313 |
| Date | January 2023 |
| Creators | Wennerblom, David, Arronet, Andrey |
| Publisher | Jönköping University, JTH, Avdelningen för datateknik och informatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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