论文标题
使用密度深度图的3D图像的深度分层：基于阈值的方法
Depth-wise layering of 3d images using dense depth maps: a threshold based approach
论文作者
论文摘要
长期以来，图像分割一直是计算机视觉中的一个基本问题。深度分层是一种分割，它以深度序列切片，与传统的图像分割问题不同，与表面分解的传统图像分割问题不同。提出的深度分层技术使用静态场景的单个深度图像将其切成多层。该技术采用阈值方法将密集深度图的行分段分为较小的分区，称为本文。然后，它使用线段标记方法来独立识别场景的对象和层。最后阶段是将场景的对象与各自的对象层联系起来。我们通过将其应用于许多图像及其密集的深度图来评估所提出的技术的效率。实验显示了有希望的分层结果。
Image segmentation has long been a basic problem in computer vision. Depth-wise Layering is a kind of segmentation that slices an image in a depth-wise sequence unlike the conventional image segmentation problems dealing with surface-wise decomposition. The proposed Depth-wise Layering technique uses a single depth image of a static scene to slice it into multiple layers. The technique employs a thresholding approach to segment rows of the dense depth map into smaller partitions called Line-Segments in this paper. Then, it uses the line-segment labelling method to identify number of objects and layers of the scene independently. The final stage is to link objects of the scene to their respective object-layers. We evaluate the efficiency of the proposed technique by applying that on many images along with their dense depth maps. The experiments have shown promising results of layering.
