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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電機工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47161
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dc.contributor.advisor陳永耀(Yung-Yaw Chen)
dc.contributor.authorSio-Sun Wongen
dc.contributor.author黃少旋zh_TW
dc.date.accessioned2021-06-15T05:49:22Z-
dc.date.available2013-08-20
dc.date.copyright2010-08-20
dc.date.issued2010
dc.date.submitted2010-08-18
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47161-
dc.description.abstract在此論文中,我們提出了一個結合分割式彩色直方圖及以卡爾曼濾波器作位置估測的多目標影像追蹤方法。遮蔽問題也在此方法中得到適當的處理。我們利用蘇恕德之兩段式背景相減法來得到移動物體的區域,接著找出各個相連的部分及把面積較小的去除。由於彩色直方圖在大小及姿態改變時有著相對穩定的優勢,因此被選為對物體外觀的一種描述。考慮到直方圖往往會損失空間的資訊,因此我們把每個物體分成上下兩部分,也就是說,每個物體被上下的紅、綠、藍,總共六個直方圖所描述。同時,隨著時間的前進,外觀模型會以指數加權移動平均的方式進行更新。另一方面,每個物體的位置都以卡爾曼濾波器進行估測。最後,我們結合外表模型及位置條件以實現追蹤。對於極具挑戰的遮蔽問題,我們也提出了一個包含合併、分開、被物體遮蔽及重新出現的新穎方法。我們也利用歷史資訊去解決嚴重甚至完全遮蔽的狀況。總的來說,這個方法可以處理物體間遮蔽及被背景物遮蔽中的長、短遮蔽,完全、部分遮蔽等問題。從眾多不同的實驗可以看到所提出的方法的強健度。zh_TW
dc.description.abstractA multi-target visual tracking approach, which consists of segmented color histograms, position estimation by Kalman filter and occlusion handling, is proposed in this thesis. The moving object regions are extracted by using Su’s Two-Staged Background Subtraction approach. Connected components are located and those of small area are discarded. Color histograms are used as descriptors of an object’s appearance due to their intrinsic benefits of being relatively scale-invariant and posture-invariant. In order to resolve the problem of losing spatial information due to histogram, an object is segmented into the upper and lower parts. Thus, the objects’ appearances are described by six histograms, namely, R, G, B histograms corresponding to the abovementioned two parts. The appearance model is then updated through Exponentially Weighted Moving Average across time. Furthermore, Kalman filter is used for position estimation for each object. We combined the appearance model and position condition to implement the tracking approach. In view of the challenging occlusion problem, a novel approach consists of Merge, Split, Obstructed and Reappeared is proposed. Historical information is utilized such that severe and even full occlusions can be handled. By and large, this approach can handle long, short, full, partial occlusions efficiently for both inter-object occlusion and occlusion by obstructors. Various experiments verify the robustness of our approach.en
dc.description.provenanceMade available in DSpace on 2021-06-15T05:49:22Z (GMT). No. of bitstreams: 1
ntu-99-R97921007-1.pdf: 4920322 bytes, checksum: 76174de423230caf0489a9324393f442 (MD5)
Previous issue date: 2010
en
dc.description.tableofcontents摘要 I
Abstract II
Contents IV
List of Figures VII
List of Tables XII
Chapter 1 Introduction 1
1.1 Motivation and Problem Definition 1
1.2 Thesis Overview 2
Chapter 2 State-of-the-Art 4
2.1 Feature Selection for Tracking Approach 4
2.1.1 Color 5
2.1.2 Edges 6
2.1.3 Contour 7
2.1.4 Optical Flow 9
2.1.5 Texture 9
2.2 Object Tracking 10
2.2.1 Kernel Tracking 11
2.2.2 Silhouette Tracking 18
2.3 State Estimation 22
2.3.1 Kalman Filter 22
2.3.2 Particle Filter 26
2.4 Occlusion Handling 30
Chapter 3 Proposed Approach 37
3.1 Moving Object Detection 38
3.2 Data Structure of an Object 42
3.3 Feature Extraction 43
3.3.1 Appearance Modeling 44
3.3.2 Position Condition 53
3.4 Feature Matching and Occlusion Handling 55
3.4.1 Feature Matching Criterion 56
3.4.2 Occlusion Handling 59
3.5 Database Update 67
Chapter 4 Results 69
4.1 Experiments without Occlusion 71
4.2 Experiments with Occlusion 78
4.3 Experiments in Real Scenes 86
Chapter 5 Conclusions and Discussions 92
5.1 Conclusions 92
5.2 Discussions and Future Work 93
References 95
dc.language.isoen
dc.subject遮蔽處理zh_TW
dc.subject分割式彩色直方圖zh_TW
dc.subject卡爾曼濾波器zh_TW
dc.subject背景相減zh_TW
dc.subject外觀模型zh_TW
dc.subject模型更新zh_TW
dc.subjectappearance modelingen
dc.subjectocclusion handlingen
dc.subjectmodel updateen
dc.subjectsegmented color histogramsen
dc.subjectbackground subtractionen
dc.subjectKalman filteren
dc.title以分割式直方圖及卡爾曼濾波器為基礎並結合遮蔽處理之多目標影像追蹤zh_TW
dc.titleMulti-target Visual Tracking Based on Segmented Histograms and Kalman Filter with Occlusion Handlingen
dc.typeThesis
dc.date.schoolyear98-2
dc.description.degree碩士
dc.contributor.oralexamcommittee傅立成(Li-Chen Fu),顏家鈺(Jia-Yush Yen),林進燈(Chin-Teng Lin)
dc.subject.keyword分割式彩色直方圖,卡爾曼濾波器,背景相減,外觀模型,模型更新,遮蔽處理,zh_TW
dc.subject.keywordsegmented color histograms,Kalman filter,background subtraction,appearance modeling,model update,occlusion handling,en
dc.relation.page102
dc.rights.note有償授權
dc.date.accepted2010-08-19
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept電機工程學研究所zh_TW
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