Swimmer position estimation by lane rectification
Takayuki Tsumita, Hidehiko Shishido, Itaru Kitahara, Yoshinari Kameda · International Workshop on Advanced Image Technology (IWAIT) 2019 · 2019
A new method of estimating swimmer position in swimming pool video is proposed. The video of swimming games is taken from a higher seat row in audience seat area. It can cover the whole field of a swimming pool. The swimming pool video is transformed so that each lane can be analyzed along with the lane direction. The foreground region that includes both the swimmer and their water splash is extracted by adaptive background modeling and by setting the mask region to cope with the influence of the non-planer water surface. Then, based on the color analysis on water splash, swimmer region can be successfully extracted. The position is estimated as the center of the Gaussian distribution of the swimmer region. The proposed method was applied to a nationwide swimming game.