Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms.

中文翻译：

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基于分段平面曲面片的交互式对象建模。

检测 3D 中的平面等元素对于描述机器人和增强现实等应用的对象至关重要。虽然平面估计得到了很好的研究，但桌面场景展示了大量的平面，并且方法通常锁定在一个主导平面上，或者不估计 3D 对象结构，而仅估计单个平面的单应性。在本文中，我们将 MDL 引入到使用跟踪的图像序列中的兴趣点在场景中增量检测多个平面补丁的问题。平面补丁被重建并存储在基于关键帧的图形结构中。在发生不同运动的情况下，根据当前可见的补丁和先前帧中看到的补丁对单独的对象假设进行建模。我们在牛津大学视觉几何组发布的标准数据集 [24] 和我们自己的包含桌面场景的数据集上评估我们的方法。结果表明，我们的方法显着改进了最先进的算法。