Robust Camera Calibration for Sport Videos using Court Models

Farin, Dirk ; Krabbe, Susanne ; Effelsberg, Wolfgang ; With, Peter H. N. de

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Document Type: Conference or workshop publication
Year of publication: 2004
Book title: Storage and retrieval methods and applications for multimedia 2004 : 20 - 22 January 2004, San Jose, California, USA ; proceedings of electronic imaging, science and technology
The title of a journal, publication series: Proceedings of SPIE
Volume: 5307
Page range: 80-91
Publisher: Yeung, Minerva M.
Place of publication: Bellingham, WA
Publishing house: SPIE
ISBN: 0-8194-5210-6
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik IV (Effelsberg -2017)
Subject: 004 Computer science, internet
Abstract: We propose an automatic camera calibration algorithm for court sports. The obtained camera calibration parameters are required for applications that need to convert positions in the video frame to real-world coordinates or vice versa. Our algorithm uses a model of the arrangement of court lines for calibration. Since the court model can be specified by the user, the algorithm can be applied to a variety of different sports. The algorithm starts with a model initialization step which locates the court in the image without any user assistance or a-priori knowledge about the most probable position. Image pixels are classified as court line pixels if they pass several tests, including color and local texture constraints. A Hough transform is applied to extract line elements, forming a set of court line candidates. The subsequent combinatorial search establishes correspondences between lines in the input image and lines from the court model. For the succeeding input frames, an abbreviated calibration algorithm is used that predicts the camera parameters for the new image and optimizes them using a gradient-descent algorithm. We have conducted experiments on a variety of sport videos (tennis, volleyball, and goal area sequences of soccer games). Video scenes with considerable difficulties were selected to test the robustness of the algorithm. Results show that the algorithm is very robust to occlusions, partial court views, bad lighting conditions, or shadows.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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