一种基于两阶段鲁棒统计的多类型特征时间配准方法

Gilles Simon, M. Berger
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引用次数: 59

摘要

提出了一种模型配准系统,能够对图像序列中已知模型的目标进行跟踪。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,线和自由形式曲线),即使在跟踪错误发生时也能够给出正确的姿态估计。在一个增强现实项目中验证了该系统的可靠性。
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A two-stage robust statistical method for temporal registration from features of various type
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.
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