任务驱动的屋顶多边形提取感知组织

C. Jaynes, F. Stolle, R. Collins
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引用次数: 93

摘要

提出了一种提取单眼航拍图像中平面多边形屋顶的新方法。使用感知分组技术提取结构特征并分层关联。使用自顶向下的特征验证,以便用图像中的局部信息验证特征和特征之间的链接,并在图中加权。图中的周期对应于可能的建筑物屋顶假设。虚拟特征被假设为部分遮挡屋顶的感知完成。提取建筑物屋顶假设的“最佳”分组特征是一个图搜索问题。图中权重最大的独立循环集被提取为最终的顶边界集。
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Task driven perceptual organization for extraction of rooftop polygons
A new method for extracting planar polygonal rooftops in monocular aerial imagery is proposed. Structural features are extracted and hierarchically related using perceptual grouping techniques. Top-down feature verification is used so that features, and links between the features, are verified with local information in the image and weighed in a graph. Cycles in the graph correspond to possible building rooftop hypotheses. Virtual features are hypothesized for the perceptual completion of partially occluded rooftops. Extraction of the "best" grouping features into a building rooftop hypothesis is posed as a graph search problem. The maximally weighted, independent set of cycles in the graph is extracted as the final set of roof boundaries.<>
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