Constraint-based sensor planning for scene modeling
Constraint-based sensor planning for scene modeling
复制标题
用于场景建模的基于约束的传感器规划
DOI：
10.1109/cira.1999.810008
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
P. Allen
中科院分区：
文献类型：
--
作者：
Michael K. Reed;P. Allen
我们描述了一个自动化的场景建模系统，由两个组件以交错的方式操作：增量建模器和传感器规划器，分析得到的模型，并计算下一个传感器的位置。该规划组件是目标驱动的，并且使用关于场景中的成像表面和未探索空间的模型信息来计算传感器位置。该方法是形状无关的，并使用一个连续的空间表示，保持感测数据的准确性。它能够通过重复规划传感器位置来完全获取场景，利用部分模型来确定未探索场景的连续区域的可见性体积。这些可见性体积与传感器放置约束相结合，以保证提高模型质量的完整的无遮挡传感器位置集。我们展示了包含多个具有高遮挡的不同对象的场景的获取结果。
We describe an automated scene modeling system that consists of two components operating in an interleaved fashion: an incremental modeler and a sensor planner that analyzes the resulting model and computes the next sensor position. This planning component is target-driven and computes sensor positions using model information about the imaged surfaces and the unexplored space in a scene. The method is shape-independent and uses a continuous-space representation that preserves the accuracy of sensed data. It is able to completely acquire a scene by repeatedly planning sensor positions, utilizing a partial model to determine volumes of visibility for contiguous areas of unexplored scene. These visibility volumes are combined with sensor placement constraints to complete sets of occlusion-free sensor positions that are guaranteed to improve the quality of the model. We show results for acquisition of a scene that includes multiple, distinct objects with high occlusion.