Sports Camera Pose Refinement Using an Evolution Strategy

• URL: http://arxiv.org/abs/2211.02143v2
• Date: Mon, 9 Oct 2023 13:49:28 GMT
• Title: Sports Camera Pose Refinement Using an Evolution Strategy
• Authors: Grzegorz Rype\'s\'c, Grzegorz Kurzejamski, Jacek Komorowski
• Abstract summary: We develop a neural network architecture for an edge or area-based segmentation of a sports field. We implement the evolution strategy, which purpose is to refine extrinsic camera parameters given a single, segmented sports field image. Experimental comparison with state-of-the-art camera pose refinement methods on real-world data demonstrates the superiority of the proposed algorithm.
• Score: 0.4910937238451484
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents a robust end-to-end method for sports cameras extrinsic parameters optimization using a novel evolution strategy. First, we developed a neural network architecture for an edge or area-based segmentation of a sports field. Secondly, we implemented the evolution strategy, which purpose is to refine extrinsic camera parameters given a single, segmented sports field image. Experimental comparison with state-of-the-art camera pose refinement methods on real-world data demonstrates the superiority of the proposed algorithm. We also perform an ablation study and propose a way to generalize the method to additionally refine the intrinsic camera matrix.

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