A novel algorithm, called semantic line combination detector (SLCD), to find an optimal combination of semantic lines is proposed in this paper. It processes all lines in each line combination at once to assess the overall harmony of the lines. First, we generate various line combinations from reliable lines. Second, we estimate the score of each line combination and determine the best one. Experimental results demonstrate that the proposed SLCD outperforms existing semantic line detectors on various datasets. Moreover, it is shown that SLCD can be applied effectively to three vision tasks of vanishing point detection, symmetry axis detection, and composition-based image retrieval. Our codes are available at https://github.com/Jinwon-Ko/SLCD.

翻译：本文提出了一种名为语义线组合检测器（SLCD）的新算法，用于寻找最优的语义线组合。该算法能够同时处理每个线组合中的所有线条，以评估线条的整体和谐度。首先，我们从可靠线条中生成多种线组合。其次，我们估算每个线组合的得分，并确定最佳组合。实验结果表明，所提出的SLCD在多个数据集上均优于现有语义线检测器。此外，研究还表明SLCD可有效应用于消失点检测、对称轴检测和基于构图的图像检索这三项视觉任务。我们的代码可在https://github.com/Jinwon-Ko/SLCD获取。