Abstract

Projections on moving objects have a problem in that the projection may slip because of the delay between tracking and projection. Here, we propose a new prediction method combining a Kalman filter and a three-frame feedback model that switches between these models according to the ball’s state of motion. We developed a real-time tracking and projection system named “Ballumiere”, which uses motion capture cameras for tracking and multiple projectors for spherical projection. We conducted a comparative experiment with an existing prediction model and showed that our method minimizes slipping and increases the accuracy of the projection.

Video

Citarion format

Shio Miyafuji, Masato Sugasaki, and Hideki Koike. 2016. Ballumiere: Real-Time Tracking and Spherical Projection for High-Speed Moving Balls. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces (ISS ‘16). Association for Computing Machinery, New York, NY, USA, 33–37. https://doi.org/10.1145/2992154.2992181