臺灣博碩士論文加值系統

近年來情境認知計算(context-aware computing)越來越突現，主要的目的是在當情境資訊(context information)改變時系統要如何去傳送合適的服務給使用者。而服務必須依賴情境資訊的取得，因此，拓展新的情境資訊對於情境認知計算的應用領域來說是一項重要的任務。有鑑於此，本論文提出了一個以影像為基礎的方位資訊(direction information)，由此可得知行動裝置所面對的方位，其原理是藉由行動裝置所得來的即時影像經過偵測及編碼後取得天際線碼(稱為SCode)，再從天際線碼中挑選出轉折點(稱為TP)與360度環場影像的轉折點進行比對。本論文中也使用了一個動態臨界值(Dynamic Threshold)的技術來克服雲層、亮度等因素對於天際線的影響。從六個不同地點的實驗結果來看，當方位誤差容忍度在15個pixels時(相當於7.5度)，其平均的方位準確度可以達到84％，並且在400MHz CPU的Pocket PC上執行，其平均時間只有1.6秒，這說明了本論文所提出的方法能夠提供有效率並且準確的方位情境資訊。

Context-aware computing is getting emergent in recent years. It focuses on how the system can deliver suitable services as the change of context information. The services rely on the available context information. The development of new context information is an important task for extending the application domain of context-aware computing. In this paper, an image-based approach for generating the direction information of a mobile device is proposed. The direction information is generated by matching the real-time image from a mobile device and 360�a surrounding image at a specific site. The matching is based on the skylines of two images. The skyline is detected and encoded into a series of codes (SCode). A set of turning points (TPs) is then selected from the SCodes. A dynamic threshold technique is also designed to overcome the influence of cloud, brightness, etc. From the experimental results of six different sites, the average accuracy is 84 percent when the inaccuracy level is fifteen pixels. The average execution time is only 1.6 second on Pocket PC with 400MHz CPU. It illustrates that the proposed approach is effective and efficient to generate direction information for context-aware computing.

中文摘要 I
Abstract II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 簡介 1
第二章 相關研究 6
第三章 方法 12
3.1 影像前處理 14
3.2 天際線偵測 15
3.3 天際線編碼 20
3.4 轉折點挑選 20
3.5 轉折點比對 23
第四章 實驗設計與結果 29
第五章 結論與未來研究 36
參考文獻 38
附錄A ：測試影像天際線偵測結果 41
附錄B ：各景點方位判斷之測試影像 43
附錄C ：各景點方位判斷之實驗結果 49

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