Ski jumping has continuously raised major public interest since the early 70s of the last century, mainly in Europe and Japan. The sport undergoes high-level analysis and development, among others, based on biodynamic measurements during the take-off and flight phase of the jumper. We report on a vision-based solution for such measurements that provides a full 3D trajectory of unique points on the jumper's shape. During the jump synchronized stereo images are taken by a calibrated camera system in video rate. Using methods stemming from video surveillance, the jumper is detected and localized in the individual stereo images, and learning-based deformable shape analysis identifies the jumper's silhouette. The 3D reconstruction of the trajectory takes place on standard stereo forward intersection of distinct shape points, such as helmet top or heel. In the reported study, the measurements are being verified by an independent GPS measurement mounted on top of the Jumper's helmet, synchronized to the timing of camera exposures. Preliminary estimations report an accuracy of +/-20 cm in 30 Hz imaging frequency within 40m trajectory. The system is ready for fully-automatic on-line application on ski-jumping sites that allow stereo camera views with an approximate base-distance ratio of 1:3 within the entire area of investigation.

Date Published: 18 January 2010
PDF: 12 pages
Proc. SPIE 7539, Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques, 753908 (18 January 2010); doi: 10.1117/12.838141

Published in SPIE Proceedings Vol. 7539:
Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)