視覺感測網路乃由許多具方向性的視覺感測器(如攝像感測器)所組成，有別於以全向性或量測性感測器所組成的一般無線感測網路。視覺感測網路的條件特性亦與一般全向性無線感測網路不同，尤其是在感測覆蓋範圍方面的差異上。視覺感測網路的感測覆蓋範圍不僅與所佈建的感測器位置相關，亦與感測器的感測方向和感測角度大小相關。此外，運用視覺感測網路進行目標追蹤的任務也高度地與視覺感測器的視覺覆蓋範圍以及影像擷取清晰狀況相關聯。本論文針對廣闊區域下運用大規模視覺感測網路進行之監控應用，提出基於Voronoi圖形特性的覆蓋範圍與目標追蹤議題解決方法。Voronoi圖主要特性是能夠將一個已知的感測區域劃分為眾多小區域(稱作Voronoi圖格)，每個圖格中僅會出現一個感測器(稱作該圖格的關聯感測器)，並且一個圖格中的任意一點與該關聯感測器之間的距離必定小於該點與任何其他感測器的距離。目前我們僅發現一篇有向性感測網路覆蓋範圍之相關研究有使用到Voronoi圖，而在視覺感測網路目標追蹤方面則並未有相關研究使用到Voronoi圖。基於Voronoi圖的特性以及其尚未普遍運用於視覺感測網路的議題上，因此本論文運用Voronoi圖的特性觀念並提出視覺感測網路覆蓋範圍提升演算法與目標追蹤遞換協定，使得在整體感測範圍、目標偵測延遲、目標追蹤率、目標追蹤距離等數個方面上皆獲得良好效能表現。
本論文所提出的方法中乃使用分散式Voronoi圖格建構方式來取代一般常見之集中式Voronoi圖建構方式，使得所提出的各演算方法皆為分散式的，並且不需要任何全域資訊。使用分散式Voronoi圖格建構方式同時也使得本論文中所提的演算方法具有容錯和優雅降級運作之優勢，即使部分感測器失效時，演算方法與視覺感測網路任務仍能繼續運作。基於分散式Voronoi圖格之建置，本論文進一步提出的四項主要研究分別如下：首先，提出了四個基本且基於Voronoi圖與Delaunay三角化圖兩種幾何圖形的不同感測覆蓋提升演算法，以比較並探索其覆蓋效能表現。其二，提出運用Voronoi圖之進階覆蓋提升演算法以進一步提升視覺感測網路之整體感測覆蓋率。其三，進一步針對行動式視覺感測網路(由可移動式視覺感測器組成)提出適用之基於Voronoi圖的感測覆蓋提升方法。最後，在感測覆蓋率提升之基礎下，整合提出單一感測器目標定位且同樣基於Voronoi圖之目標追蹤遞換協定。這些提出的方法經由模擬，與不同方法進行評估比較，皆能在感測覆蓋率與目標追蹤方面獲得良好之提升改善。本論之貢獻乃在於針對未來潛在的廣域性大規模視覺感測網路監控應用，提出具可行性且整合了分散式覆蓋提升與目標追蹤遞換協定之方法。

A visual sensor network (VSN) consists of directional visual sensors, typically camera sensors, instead of omnidirectional or scalar sensors in wireless sensor networks (WSNs). The conditions of a VSN are dissimilar from those of an omnidirectional WSN, especially on the sensing coverage. The sensing coverage of a VSN depends on not merely the locations but also the directionality and sensing angle of the deployed sensors. In addition, the achievement of target tracking by a VSN highly depends on the visual coverage and acquired image clarity of the visual sensors. This dissertation aims at the coverage and target tracking issues and proposed Voronoi Diagram-based solutions for the surveillance application of wide-area large-scale VSNs. A Voronoi Diagram can divide a given region into sub-regions, thus Voronoi cells. Each cell is associated with only one sensor and any point in the cell has a shorter distance from the associated sensor than those from the other sensors. There is only one related work of using Voronoi Diagram to enhance the coverage of a directional sensor networks (DSN). With regard to the VSN target tracking, Voronoi Diagram has not utilized in related works. In brief, Voronoi Diagram has not drawn much attention in the VSNs. Hence this dissertation utilizes the concept and characteristic of a Voronoi Diagram and proposes coverage improvement algorithms and target tracking handover protocol for VSNs to perform a better performance in the criteria of working coverage, target-detected latency, target-tracked ratio and target tracking distance.
The proposed scheme constructs local Voronoi cells by using a distributed method which is different from the conventional centralized construction of a Voronoi Diagram. Hence the algorithms proposed in this dissertation are all distributed and need no global information. The distributed Voronoi cell construction also can bring the benefits of fault tolerance and graceful degradation to adapt the proposed algorithms to the occurrence of sensor malfunction. Four major works were completed based on the construction of distributed Voronoi cells. The first is four basic algorithms using Voronoi Diagram and Delaunay Triangulation; and to compare and explore their coverage performances. The second is to propose an advanced Voronoi-based improvement algorithm for VSN sensing coverage. The third aims at a mobile VSN consists of mobile visual sensors to propose a coverage improvement approach. The final is a Voronoi-based handover protocol for target tracking in a VSN. The proposed schemes in this dissertation were also evaluated and compared with other different methods and the performance results show that they have good improvements. The contribution of this dissertation is to provide a well-performed and distributed approach on sensing coverage and target tracking topics for the wide-area surveillance applications of large-scale VSNs.

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