[Papers] Method of Multiview Video Switching for Soccer Game Analysis in Large Scale Space
Hidehiko Shishido, Yosuke Okada, Yoshinari Kameda, Masaaki Koido, Itaru Kitahara · ITE Transactions on Media Technology and Applications · 2020
Research on tactical and performance analysis utilizes videos of dynamic sports scenes. An effective multiview video switching method can support the analysis. Bullet-time video is a multiview video browsing approach. Because the image is presented almost as it is, it is suitable for high-quality observations of the subject from multiple directions. This paper proposes a multiview image switching method for understanding dynamic scenes in large-scale spaces such as soccer games. We develop a prediction model for the camerawork for shooting Bullet-time videos. The model using deep neural network, which can estimate a suitable viewpoint to observe the target scene from the position information of the soccer players, ball, and goals.