半管運動電視轉播影片之事件偵測技術

Abstract

本文中，一個低成本和高效率的系統性自動分析半管運動轉播影片方法被提出來。除了場地顏色覆蓋比率，我們發現玩家區域使用顯著目標偵測機制可面對半管運動影片模糊場景的挑戰。此外，基於現有的MPEG 壓縮的影片原生的運動向量（motion vector）我們提出一種可用於偵測旋轉（spin）事件的新穎且有效的方法。實驗結果表明，該系統能有效在半管影片中識別難以被檢測到的旋轉（spin）和滑行（grind）等事件。

In this work, a low-cost and efficient system is proposed to automatically analyze the halfpipe sports broadcasting videos. In addition to the court color ratio information, we find the player region by using salient object detection mechanisms for facing the challenge of motion blurred scenes in HP videos. Besides, a novel and efficient method for detecting the spin event is proposed on the basis of native motion vectors existing in MPEG compressed video. Experimental results show that the proposed system is effective in recognizing the hard-to-be-detected spin and grind events in halfpipe videos.