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系統識別號 U0026-0206201013302600
論文名稱(中文) 連續手語之自適應手勢追蹤
論文名稱(英文) Adaptive Tracking of Gestures for Continuous Sign Language
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 98
學期 2
出版年 98
研究生(中文) 董郁華
研究生(英文) Yu-Hua Dong
學號 p7697131
學位類別 碩士
語文別 中文
論文頁數 36頁
口試委員 口試委員-張景新
口試委員-連震杰
口試委員-賴文能
指導教授-謝璧妃
中文關鍵字 粒子濾波器  等位函數法  形狀先驗 
英文關鍵字 Particle Filter  Level Set  Shape Prior 
學科別分類
中文摘要 手語有四十九種基本手型,加上軌跡有各種不同的意思,所以辨識手語主要可以分成兩大類,追蹤軌跡與辨識手型。手勢是一種最自然的溝通方式,因此手勢辨識一直是熱門的研究領域。台灣手語擁有一組有限且定義清楚的手勢,因此適合應用在手勢辨識上。非靜態的手語由於雙手在三維空間任意移動時常伴隨著遮蔽的問題。遮蔽的問題在於當兩物體的位置於二維影像上發生重疊時,造成較後方的物體在影像上被遮蔽無法完整呈現,而不完整的資訊會影響到最後辨識的結果。
追蹤台灣手語軌跡中的問題是遮蔽,當遮蔽發生時要辨識出追蹤的物體是否為真正的目標是困難的。如果無有力的特徵時,即使手在很短的時間內被遮蔽,追蹤目標有可能發生漂移或失敗。長時間準確的追蹤是一項艱鉅的挑戰。在這項工作中,我們使用粒子濾波器與等位函數法模型去追蹤雙手,我們提出一個新的且有效率與完備的追蹤演算法並可處理部分遮蔽。
實驗中選取了會發生遮蔽情形的手語影帶測試,結果顯示手的形狀能幫助追蹤到正確的目標,並且增加了準確率。
英文摘要 There are 49 kinds of basic hand shape in Taiwanese Sign Language (TSL), it may convey different meaningful information depending on the trajectory of two hands. So, sign language recognition mainly can be divided into two categories, tracking and identification in hand shape. Recognition of Taiwanese sign language is completely defined by a set of gestures and is a typical application of gesture recognition. In recognition of dynamic sign language, a difficult problem arises when two moving hands in the 2D image appear overlapped partially. The occurrence of occlusion yields deficient silhouette of hand shapes, leading to indigent recognition results.
One of the problems for tracking trajectory of Taiwanese Sign Language is occlusion. It is difficult to recognize whether the object being followed by the tracker is really target when occlusion occurs. Without effective features, the tracker is likely to drift away or fail gradually when the hand is occluded even if a short duration of time. Long duration robust tracking is a great challenge. In this work, we use particle filter with level set based models to track hands. We present a new algorithm for robust and efficient tracking by handling partial occlusions.
In the experiment, we chose sign words associated with hand occlusion for test. The results show that the shape can assist to track the really target, and improve the accuracy.
論文目次 1. 序論 1
1.1 研究背景 1
1.2 研究目的與重要性 3
1.3 章節概要 6
2. 相關研究 7
2.1 聯結粒子濾波器 7
2.2 複雜背景之手形擷取 9
2.2.1 等位函數法─物體輪廓追蹤 10
2.2.2 擬用方法 12
2.2.2.1. 弱邊界另訂一新類別 13
2.2.2.2. 混合高斯擬合項 14
2.2.3 形狀先驗的改良 14
3. 研究方法 16
3.1 擬用方法 16
3.1.1 動態模型 16
3.1.2 運動狀態的定義 16
3.1.3 運動狀態的轉換 17
3.1.4 速度於各運動狀態下之機率密度函數 19
3.2 演算法 21
3.2.1 初始化 21
3.2.2 預測 21
3.2.3 更新 22
4. 實驗結果與討論 25
4.1 資料數據描述 25
4.1.1 單字手語資料 25
4.1.2 句子手語資料 26
4.2 手語追蹤軌跡實驗 27
5. 結論與未來研究方向 32
參考文獻 34



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