mlsanityData to 14 Oct 2026

Accurate Tennis Court Line Detection on Amateur Recorded Matches

arXiv 2404.06977 ↗First posted 10 Apr 2024cs.CVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 5 references that are in the map. First posted on arXiv 10 Apr 2024.

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2 of 5 references.

References · 2

  1. 2023ShadowFormer: Global Context Helps Image Shadow Removalcited by 35
  2. 2019Optimizing Through Learned Errors for Accurate Sports Field Registrationcited by 19

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