Visual planes-based simultaneous localization and model refinement for augmented reality
Visual planes-based simultaneous localization and model refinement for augmented reality
复制标题
基于视觉平面的增强现实同步定位和模型细化
DOI：
10.1109/icpr.2008.4761313
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Isabelle Marchal
中科院分区：
文献类型：
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作者：
Fabien Servant;É. Marchand;P. Houlier;Isabelle Marchal
本文提出了一种基于场景局部知识的摄像机姿态跟踪方法。该方法是基于单目视觉同时定位和地图（SLAM）。相对于经典的SLAM实现，这种方法使用先前已知的关于环境的信息（墙壁的粗略地图），并从各种可用的数据库和蓝图中获益以约束问题。该方法认为跟踪的图像块属于已知平面（在其定位中具有一些不确定性），并且SLAM地图可以由相机和平面的关联来表示。在本文中，我们提出了一个适应SLAM实现和详细考虑模型。我们表明，这种方法给出了良好的效果，一个真实的序列与复杂的运动增强现实（AR）的应用。
This paper presents a method for camera pose tracking that uses a partial knowledge about the scene. The method is based on monocular vision simultaneous localization and mapping (SLAM). With respect to classical SLAM implementations, this approach uses previously known information about the environment (rough map of the walls) and profits from the various available databases and blueprints to constraint the problem. This method considers that the tracked image patches belong to known planes (with some uncertainty in their localization) and that SLAM map can be represented by associations of cameras and planes. In this paper, we propose an adapted SLAM implementation and detail the considered models. We show that this method gives good results for a real sequence with complex motion for augmented reality (AR) application.