追蹤物體在電腦視覺上一直以來都是一個很重要的題目，本文裡我們提出一個改善CAMSHIFT的物件追蹤方法。我們使用2D histogram 包含Hue 和亮度資訊來描述目標的特徵，使用此方式能夠解決影像品質不好和具有achromatic像素點的問題。方法中並使用flooding演算法和貢獻度計算，使獲得的直方圖可以如實反映出目標的色彩資訊和各個色彩對前景和背景的辨識度。為了能適應的前景/背景的變化，我們提出更新ROI尺寸和目標直方圖的方法。實驗結果顯示，我們所提出的方法比現有的方法，能保有穩定且令人滿意的結果。 In this paper, we present an improved version of CAMSHIFT algorithm. We use a 2D histogram including hue and brightness to describe the color feature of the target. In this way, videos with poor quality or achromatic points can be better characterized. The Flooding process and contribution evaluation are used to obtain a precise target histogram which reflects true color information and discrimination ability. To be adaptive to the foreground/background variation, formula for updating ROI size and target histogram are proposed. The proposed method is compared with existing methods and shows steady and satisfactory results.
