近年來擴增實境技術發展迅速，已成功應用於工程、行銷、娛樂與醫療等不同領域，然而在即時性視覺化內容呈現上，仍有許多難題尚未解決。本研究針對結合深度攝影機（RGB-D Camera）的擴增實境，特別是虛擬產品展示的應用，進行不同面向的效能改善。以 RGB-D 攝影機取得真實場景的三維資訊，根據使用者由場景中選擇的定位參考，可自動進行無標籤定位追蹤初始化，再藉由不同座標系的轉換計算，將虛擬模型準確擺置於實際場景影像中。此外根據即時性的場景深度資料，可正確處理虛擬模型與真實物件的遮蔽關係，產生更真實的虛實互動內容。現行的 RGB-D 攝影機存在隨機雜訊與深度缺失的問題，故提出改善深度資訊品質的計算流程，除可修補缺失之深度資訊點外，亦可降低因連續畫面的差異，所導致的遮蔽邊緣跳動。另一方面，為提高虛擬產品展示的應用價值，發展一項分散式擴增實境系統雛形，結合雲端服務與平行處理技術，實現大量遠端虛擬試穿的使用情境。本研究針對現行擴增實境技術的缺失，提出可行的改善方法，將可有效提升虛實內容的互動性。

Progressing rapidly in recent years, augmented reality (AR) technologies have successfully found applications in engineering, marketing, entertainment, and medical industries. However, to render high-quality visualization contents in AR remains a challenging task with several technical barriers. Recent development of RGB-D cameras may provide an effective approach to solving those difficulties by capturing real-time depth data of a real scene. This research attempts to improve the effectiveness of product display in AR from multiple perspectives. First, a virtual model can be precisely positioned into a real scene according to the reference geometry selected by users from the scene, without use of markers. Mutual occlusions between real and virtual objects can be precisely estimated using the depth data. This information enables realistic interactions in an AR environment with intuitive rendering of both. In addition, a computational framework is developed to overcome data deterioration induced by random noises and missing pixels in the data captured by RGB-D cameras. The framework effectively reduces the jitter problem occurring along the occlusion boundaries. In addition, we implement a distributed AR system to realize the concept of mass virtual try-on. This system integrates cloud computing and parallel processing technologies to increase the computation efficiency involving in the try-on application. A use scenario of shoes try-on demonstrates the feasibility of the system. This work enhances the realistic extent of interactions between real and virtual contents by integrating RGB-D cameras into AR applications.

目錄
摘要
目錄
圖目錄
表目錄
第一章、緒論
1.1 研究背景
1.2 文獻探討
1.2.1 擴增實境中的虛實互動
1.2.2 擴增實境中的物件追蹤與定位
1.2.3 基於行動裝置之虛實互動服務
1.3 研究目的
第二章、系統架構
2.1 系統概念架構
2.2 三維資訊修復模組
2.3 虛實互動改善模組
2.4 分散式虛擬鞋品試穿戴雛型系統
2.5 小結
第三章、三維資訊修復模組
3.1 三維資訊感測
3.2 三維資訊修復
3.2.1 深度資訊裁剪與映射
3.2.2 三維資訊補缺與降噪
3.3 三維資訊修復結果
3.4 小結
第四章、虛實互動改善模組
4.1繪圖像素點與三維點群校正
4.2 無標記定位
4.2.1 位置初始化
4.2.1 最小平方法之三維點群平面迴歸
4.3 虛擬模型之剛體轉換
4.3.1 虛擬模型座標系定義
4.3.2 座標轉換
4.3.3 虛擬模型之動態調整
4.4 虛擬模型遮蔽效果
4.4.1 虛擬模型與點群之關係
4.4.2 三維點群緩衝檢查
4.5 虛擬模型遮蔽邊緣平滑化
4.5.1 虛擬模型遮蔽像素區域提取
4.5.2 虛擬模型遮蔽輪廓邊緣偵測
4.5.3 遮蔽區域之近似多邊形計算
4.5.4 遮蔽效果連續性提升
4.6 小結
第五章、分散式虛擬鞋品試穿戴雛型系統
5.1 RGB-D 三維資料結構
5.1.1 PCD 資料結構
5.2 虛擬鞋品試穿技術之模組化
5.2.1 三維影像擷取模組
5.2.2 虛擬鞋品試穿戴計算模組
5.3 基於 GPU 運算之系統架構
5.3.1 GPU 運算
5.3.2 ICP 運算平行化
5.3.3 運算平台之部署
5.4 小結
第六章、系統實作
6.1 程式執行環境
6.2 三維資料修復模組
6.3 虛實互動改善模組
6.4 分散式虛擬鞋品試穿戴雛型系統
第七章、結論與未來研究工作
7.1 結論
7.2 未來展望
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