CVApr 10, 2024

Accurate Tennis Court Line Detection on Amateur Recorded Matches

arXiv:2404.06977v1
Originality Synthesis-oriented
AI Analysis

This enables automatic refereeing for amateur and professional tennis matches, though it is incremental.

The paper tackles tennis court line detection in amateur recordings by enhancing a Hough-Line-Detection algorithm with pretrained shadow-removal and object-detection models, resulting in accurate line detection on dirty courts.

Typically, tennis court line detection is done by running Hough-Line-Detection to find straight lines in the image, and then computing a transformation matrix from the detected lines to create the final court structure. We propose numerous improvements and enhancements to this algorithm, including using pretrained State-of-the-Art shadow-removal and object-detection ML models to make our line-detection more robust. Compared to the original algorithm, our method can accurately detect lines on amateur, dirty courts. When combined with a robust ball-tracking system, our method will enable accurate, automatic refereeing for amateur and professional tennis matches alike.

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