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篇名 |
Register Based on Large Scene for Augmented Reality System
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並列篇名 | Register Based on Large Scene for Augmented Reality System |
作者 | Zhen-Wen Gui |
英文摘要 | Register is steadily gaining in importance due to the drive from various computer vision applications, such as augmented reality (AR), mobile computing, and humanmachine interface. Efficient keypoint-based approachs are widely used in scene register. These approaches often model a scene as a collection of keypoints and associated descriptors, and then construct a set of correspondences between scene and image keypoints via descriptor matching. Finally, these correspondences are used as input to a robust geometric estimation algorithm such as RANSAC to find the transformation of the scene in the image. This paper focuses on designing a robust and flexible registration method for wide-area augmented reality applications. Firstly, we propose to partition the whole scene into several sub-maps according to the user’s preference or the requirements of the AR applications instead of building a global map of the wide-area scene. Secondly a linear structured SVM classifier is used to perform scene learning online, which allows us to quickly adapt our model to a given environment. Finally, a hybrid tracking strategy is implemented by combining both wide and narrow baseline techniques. Some experiments have been conducted to demonstrate the validity of our methods. |
起訖頁 | 101-113 |
關鍵詞 | Augmented reality、Wide-area registration、Scene recognition |
刊名 | 網際網路技術學刊 |
期數 | 202001 (21:1期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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