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研究生：	莊淯翔 Chuang, Yu-Hsiang
論文名稱：	自動調整的人體追蹤樣板比對法 An Auto-Tuning Template Matching for Human Body Tracking
指導教授：	郭淑美 Guo, Shu-Mei
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 資訊工程學系 Department of Computer Science and Information Engineering
論文出版年：	2010
畢業學年度：	98
語文別：	中文
論文頁數：	48
中文關鍵詞：	人體追蹤、卡曼濾波器、樣板比對、大小改變
外文關鍵詞：	Human body tracking, Kalman filter, template matching, scale changes
相關次數：	點閱：91 下載：1
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在本論文中，我們利用一種可自動調整的樣板比對法完成人體追蹤。在系統中，自動調整的樣板比對主要針對人體的大小改變以及遮蔽問題作處理。基於中間值絕對標準差的概念，我們透過顏色的資訊去計算目前的樣板以及參考樣版之間的變異數進而評估出最相似的區塊。經由此變異數，樣板的大小將可自動地調整。除此之外，此變異數同時也是評估遮蔽是否存在的標準。最後，實驗結果呈現了本系統不僅易於實做並且可以有效的評估大小改變以及判斷遮蔽是否存在。

An auto-tuning template matching for human body tracking is proposed in this thesis. Auto-tuning is incorporated in template matching for our tracking system to evaluate scale change and some occlusion problems of human body. We use the color information to evaluate the most similar region, and to compute the variance between the current template and the reference template based on the concept of median absolute deviation (MAD). According to the variance, the scale of template will be automatically adjusted well. And, the variance is also a standard to evaluate the presence of occlusion. The experimental results show that the proposed tracking system is simple to be implemented and the performance is effective in estimating scale changes and the presence of occlusion.

Table of Contents
Abstract.......................................................................................v
Table of Contents.....................................................................vii
List of Figures...........................................................................ix
Chapter 1 Introduction...........................................................1
Chapter 2 Background...........................................................6
2.1 Kalman filter................................................................................6
2.1.1 Fundamental dynamic system model…………………………………6
2.1.2 Discrete Kalman filter algorithm ……………………………………..7
2.2 Template matching.....................................................................10
2.3 Median absolute deviation........................................................13
Chapter 3 Proposed Approach..............................................14
3.1 Median absolute variance computation...................................15
3.2 Total occlusion evaluation.........................................................16
3.3 Automatic scale adjustment......................................................19
Chapter 4 Experimental Results..........................................22
4.1 Parameter assignment...............................................................22
viii
4.2 Scale change................................................................................24
4.3 Occlusion.....................................................................................33
4.4 Performance analysis.................................................................38
Chapter 5 Conclusion and Future Works............................45
5.1 Conclusion..................................................................................45
5.2 Future works..............................................................................45
Reference.................................................................................47
                                    

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校內：2011-08-16公開
校外：2011-08-16公開

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