A two-stage robust statistical method for temporal registration from features of various type
A two-stage robust statistical method for temporal registration from features of various type
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DOI：
10.1109/iccv.1998.710728
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发表时间：
1998-01
期刊：
影响因子：
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通讯作者：
Gilles Simon;M. Berger
中科院分区：
文献类型：
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作者：
Gilles Simon;M. Berger
提出了一种能够在图像序列中跟踪其模型已知的对象的模型配准系统。它集成了跟踪，姿态确定和更新的可见特征。我们系统的核心是姿态计算方法，它以非常稳健的方式处理各种特征（点，线和自由形式的曲线），即使在跟踪错误发生时也能够给出正确的姿态估计。该系统的可靠性显示在增强现实项目。
A model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. It integrates tracking, pose determination and updating of the visible features. The heart of our system is the pose computation method, which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errors occur. The reliability of the system is shown on an augmented reality project.