RGB-D几何特征提取及基于边缘的场景sifs

Bingjie Yang, E. Chen, Shou-yi Yang, Wenjuan Bai
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引用次数: 0

摘要

本文提出了一种RGB-D图像的几何特征提取方法及其在场景固有属性恢复中的应用。该方法提取几何特征,同时利用深度图中的三维形状信息和RGB图像中的边缘信息。几何特征分为遮挡边缘和褶皱边缘。该方法不仅能准确高效地提取RGB-D图像的边缘信息,而且能有效地对边缘信息进行分类。此外,我们的算法更接近于实时处理。此外,我们还提出了将这些几何特征作为基于边缘的场景固有属性恢复的应用。实验结果表明,我们提出的几何特征提取和基于边缘的场景固有属性恢复算法优于scene - sirsf算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RGB-D geometric features extraction and edge-based scene-SIRFS
In this paper, we propose a geometric features extraction approach for RGB-D image and its application in intrinsic scene properties recovery. Our approach extracts geometric features, and make use of both 3D shape information from depth map and edge information from RGB image. Geometric features are categorized as occlusion edges and fold edges. The proposed method can not only extract the edge information from the RGB-D image accurately and efficiently, but also classify the edge information effectively. Moreover, our algorithm is close to the real time processing. Besides, we present an application of these geometric features as edge-based intrinsic scene properties recovery. Experimental results demonstrate that our proposed of geometric features extraction and edge-based intrinsic scene properties recovery outperforms Scene-SIRSF algorithms.
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