隨著感測器的普及與價格降低,研究人員開始以深度感測器進行相關研究,並提供 許多有用的資訊。棒壘球投手在牛棚練習時,如果能透過輔助系統的協助將能提升投球 品質,在上場前即調整到最佳狀態。本研究以系統開發方法,使用深度感測裝置為工具, 以 13 名大專乙組棒球選手為研究對象,提出以 Kinect 為基礎的 3D 好球帶系統,該系 統能判斷球速及其品質,並發展以感測資料為主的 3D K-Zone 回放系統,進行投球軌跡 的描繪。
An increasing number of researchers have begun to use depth sensors in their studies due to the drop in sensor prices in recent years. In computer vision, depth provides a wider range of useful information. In sports, baseball and softball pitchers are typically unable to self-evaluate their throw quality when practicing in the bullpen, and umpires are mostly unavailable to evaluate their throw quality. In this context, the present study proposed a 3D strike zone system based on the Kinect v2. The system was able to determine ball speed and throw quality. Recordings were then exported into a visual ball trajectory image including a 3D K-Zone, which can service as a reference for pitchers.
深度感測;3D 好球帶;棒球
Depth Sensor; 3D K-Zone; Baseball