臺灣博碩士論文加值系統

近幾年來，隨著科技的成功發展，無線視訊感測網路的相關研究越來越盛行。動態物體追蹤的問題也廣泛的在無線視訊感測網路中研究。然而鮮少論文討論視訊感測節點所拍攝到的畫面品質如何，所以，在本篇論文中 我們的目的是在任何時間點都可以補捉到目標物體任何角度的畫面，而且最重要的是確保所拍攝到的畫面能保證有一定的品質。為了達成目的,感測的模組會與一般傳統視訊感測模組有些不同，首先，視訊感測器的感測範圍 Field of View (FoV)不會有著固定的感測長度和角度，不會特定預設他的感測範圍，而是透過影像處理Peak Signal-to-Noise Ratio (PSNR)來做品質保證，並透過PSNR的值來界定品質保證的範圍，如此一來，只要物體進到品質保證的範圍時，就可以維持拍攝到的影像資料的品質。第二，我們不對目標物體特徵事前進行假設，我們透過在任何時間點拍攝涵蓋整個物體周圍來確保任何細節不會遺漏。最後，我們同時考量時間和空間因素讓物體追蹤問題轉變成set cover問題。因為是set cover problem，所以我們提出兩個啟發式sensor-based scheme和area-based scheme的選擇節點方法來進行以畫質為前提的節能選點。根據實驗的結果，sensor-based scheme可以減少並關閉多餘的節點，藉此來節省能量，而area-based scheme則可以透過平均分散消耗來延長整體網路的壽命。本篇主要貢獻在於結合考量物體追蹤問題與影像品質問題以及全角度拍攝的問題，並且在選擇之後考量節能問題。

In recent years, with the advancement of technologies, Wireless Visual Sensor Networks (WVSNs) become a popular research. Mobile object tracking problems were widely studied in the WVSNs. However, rare works discourse the quality of images captured by visual sensors. In this paper, our goal is to track a mobile object and obtain images of the object from arbitrarily angle and time. Most importantly, quality of each image is guaranteed. To achieve this goal, some basic sensing models are different from other research. First, Field of View (FoV) of the sensor is no longer a sector with a predefined angle and radius. Without setting the sensing range, we limit the FoV according to the Peak Signal-to-Noise Ratio (PSNR). Second, we assume the feature of the object cannot be known in advance. We intend to cover the entire object all the time to make sure that every detail of the object is not missing. Finally, we model the tracking problem as a set cover problem which considers both of the spatial and time domains at the same time. We propose two heuristic sensor selection schemes, sensor-based scheme and area-based scheme. According to our simulation results, while sensor-based scheme can reduce number of redundant nodes to be selected, area-based scheme can prolong more network lifetime. In conclusion, this work tackles the moving object tracking problem by tacking the image quality and full angle view into consideration and meanwhile achieve energy conservation.

Contents
Introduction 8
Related Works 11
System Model and Network Model 14
System model 14
Network Model 16
Assumptions 18
Problem Statement 20
Basic Optical 21
Full Angle cover 29
Selection Scheme 33
Transform into set cover problem 34
Characteristics of the model 36
Sensor-based scheme 40
Area-based scheme 41
Experiment 43
Simulation 46
Conclusion and future works 51
Reference 52

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