臺灣博碩士論文加值系統

?遊地圖是專門為旅遊者所設計的一種地圖，?遊者可藉此工具探訪一個地區的熱門景點，因此一個設計良好的地圖對旅遊者而言是非常重要的。然而目前的數位?遊地圖大多是由現成的電子地圖所改編，旅遊者並無法快速且直觀地獲取熱門景點的位置及其相關資訊，因此，本研究以數位?遊地圖為研究對象，企圖找尋一種新的旅遊景點符號，來充分表達景點的特色。
目前以地理資訊為導向的影像分享平台(Geo-oriented Photo Sharing Website)日益風行，許多人將旅遊過程中所拍攝的影像上傳到影像分享平台上，例如Google Earth、Panoramio、Flickr等，這些網路平台將影像依據其地理資訊顯示在地圖上，供使用者瀏覽。本研究應用大量具有地理資訊的影像，自動化決定熱門景點的位置，並且選擇一張能充分描述景點特色的影像，作為旅遊地圖上景點的代表符號，其目的在提供?遊者正確、適當與直觀的?遊資訊。首先，熱門景點會有大量的旅遊者及拍照影像，因此可假設一個區域內，如果有大量使用者上傳的影像，則該區域可視為一個熱門景點，對此，本研究使用自動化影像分類方法，對影像的地理資訊進行分類，進而擷取出熱門景點的位置。同樣的，在一個景點內，大部分遊客所拍攝的內容都有包含該景點的特色，因此可利用影像分類演算法將同時具有形狀與色彩相似的影像分為同一類，而影像數量最多的類別則可視為含有該景點主要特色之類別，接著，從其中找出一張高品質影像來代表該景點，最後繪製出景點的位置以及其代表影像。實驗結果顯示，本方法可成功的擷取出景點位置及其代表影像，因此，本方法可實現自動化數位旅遊地圖的生成與更新。

Tourist maps are designed for tourists to visit popular hot spots such as scenic places and landmarks in unfamiliar areas. A well-designed tourist map can provide sufficient and intuitive information about hot spots for tourists. Thus, determining hot spots and their icons are important in generating tourist maps. In this paper, an automatic hot spot and icon determination approach is introduced. Compared to the general digital tourist maps that use text, simple shapes, and 3D models as symbols to represent hot spots and simply rebuild from the existing digital maps, we select photos offering abundant visual features of hot spots as image icons and in tourist maps. The photos are automatically extracted from a repository of photos downloaded from online photo-sharing communities, such as Google Earth, Panoramio, and Flickr. Hot spots and their corresponding image icons are determined by a voting strategy and a photo quality assessment approach. The basic idea is to regard each user-uploaded photo as a vote for a popular hot spot. Based on this assumption, an area with many uploaded photos is selected as a hot spot, and a view is captured frequently is regarded as a representative view. The experimental results show that the proposed approach can successfully extract hot spots and visually pleasant images to represent these spots. It demonstrates that our approach is feasible in automatic tourist map generation.

第一章、 緒論 1
1.1 研究動機與目的 1
1.2 結合影像與地理資訊網路平台簡介 2
1.3 旅遊地圖簡介 5
1.4 本研究的主要概念及貢獻 7
1.5 研究流程 8
1.6 論文架構 10
第二章、 相關研究 12
2.1 地圖符號的設計 12
2.2 網路資訊應用於旅遊景點之相關研究 14
2.3 影像特徵描述子(feature descriptor) 15
第三章、 決定景點位置之研究方法 17
3.1 影像及其對應的地理資訊 17
3.2 影像下載 19
3.3 均值移動(mean-shift)演算法 22
第四章、 影像特徵表示(feature representation) 25
4.1 形狀特徵 25
4.1.1 影像邊界偵測 25
4.1.2 階層式方向直方圖統計 29
4.2 色彩特徵 32
4.2.1 色彩空間之轉換 32
4.2.2 色彩黏著向量(color coherence vector) 34
第五章、 影像分類 39
5.1 距離量測與相似矩陣 39
5.2 正規化切割(normalized cuts)演算法 43
5.3 景點代表影像之選擇 48
第六章、 實驗成果與討論 50
6.1 實驗區影像簡介 50
6.2 熱門景點之決定成果 51
6.3 景點代表影像之選擇成果 54
6.4 實驗區之旅遊地圖 63
6.5 地圖尺度 66
6.6 問卷調查 69
第七章、 結論 74
附錄I 正規化切割(normalized cuts) 77
附錄II 問卷調查內容 82
參考文獻 89

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