Recovering Correct Reconstructions from Indistinguishable Geometry

Jared Heinly, Enrique Dunn, Jan-Michael Frahm
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引用次数: 8

Abstract

Structure-from-motion (SFM) is widely utilized to generate 3D reconstructions from unordered photo-collections. However, in the presence of non unique, symmetric, or otherwise indistinguishable structure, SFM techniques often incorrectly reconstruct the final model. We propose a method that not only determines if an error is present, but automatically corrects the error in order to produce a correct representation of the scene. We find that by exploiting the co-occurrence information present in the scene's geometry, we can successfully isolate the 3D points causing the incorrect result. This allows us to split an incorrect reconstruction into error-free sub-models that we then correctly merge back together. Our experimental results show that our technique is efficient, robust to a variety of scenes, and outperforms existing methods.
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从难以区分的几何中恢复正确的重建
运动结构(SFM)被广泛用于从无序的照片集合中生成三维重建。然而,在存在非唯一的、对称的或其他不可区分的结构时,SFM技术通常会错误地重建最终模型。我们提出了一种方法,不仅可以确定是否存在错误,还可以自动纠正错误,以便生成正确的场景表示。我们发现,通过利用场景几何中存在的共现信息,我们可以成功地隔离导致错误结果的3D点。这允许我们将不正确的重建拆分为没有错误的子模型,然后我们将它们正确地合并回一起。实验结果表明,该方法对各种场景具有较强的鲁棒性,并且优于现有方法。
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