基于多重图像判读的广义边界
Generalized Boundaries from Multiple Image Interpretations
摘要：
边界检测对于诸如分割和识别的各种计算机视觉任务是必不可少的。在本文中，我们提出了一个统一的配方和一种新的算法，适用于检测不同类型的边界，如强度边缘，遮挡边界或对象类别特定的边界。我们的配方导致一个简单的方法与国家的最先进的性能和显着降低计算成本比现有的方法。我们评估我们的算法对不同类型的边界，从低层次的边界提取的自然图像中，使用运动线索和RGB-D相机获得的遮挡边界，从软分割的边界。我们还提出了一种新的方法，可以与我们的边界检测方法结合使用的数字/地面软分割，并提高其准确性，几乎没有额外的计算成本。
英文摘要：
Boundary detection is essential for a variety of computer vision tasks such as segmentation and recognition. In this paper we propose a unified formulation and a novel algorithm that are applicable to the detection of different types of boundaries, such as intensity edges, occlusion boundaries or object category specific boundaries. Our formulation leads to a simple method with state-of-the-art performance and significantly lower computational cost than existing methods. We evaluate our algorithm on different types of boundaries, from low-level boundaries extracted in natural images, to occlusion boundaries obtained using motion cues and RGB-D cameras, to boundaries from soft-segmentation. We also propose a novel method for figure/ground soft-segmentation that can be used in conjunction with our boundary detection method and improve its accuracy at almost no extra computational cost.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
