Tracking extended objects using extrusion Random Hypersurface Models
Tracking extended objects using extrusion Random Hypersurface Models
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DOI：
10.1109/sdf.2014.6954722
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Antonio Zea;F. Faion;U. Hanebeck
中科院分区：
文献类型：
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作者：
Antonio Zea;F. Faion;U. Hanebeck
随着传感器分辨率的提高，跟踪算法的准确性和鲁棒性可以通过结合更多关于目标物体形状的信息来提高。这就提出了对能够描述详细对象的简单且鲁棒的形状模型的需求。在本文中，我们提出了一种基于随机超曲面模型的方法，将目标形状解释为缩放的挤出。这是通过将基于投影的模型与概率方法相结合，整合两种机制的优势来实现的。由于瓶、盒或容器等挤压形状在日常生活中广泛存在，因此这种方法可以应用于各种环境中的跟踪。
As sensor resolution increases, the accuracy and robustness of tracking algorithms can be improved by incorporating more information about the shape of the target object. This raises the need for simple and robust shape models capable of describing detailed objects. In this paper we propose an approach based on Random Hypersurface Models that interprets target shapes as scaled extrusions. This is achieved by combining projection-based models with probabilistic approaches, integrating the strengths of both mechanisms. As extruded shapes such as bottles, boxes, or containers can be extensively found in everyday situations, this approach can be applied for tracking in a large variety of environments.