Depth estimation using monocular cues from single image

Yasir Salih, A. Malik, Zazilah May
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引用次数: 12

Abstract

This paper investigates depth estimation using monocular cues. Human visual system uses monocular cues such as texture, focus and shading for depth perception. Our proposed algorithm is based on segmenting the image into homogenous segments (superpixels), and then out of these segments we extract the ground segment and the sky segment. These two segments guide the depth estimation by providing region with maximum depth (sky) and region with minimum depth (ground). The reset of the segments will have a depth value between the sky and ground. This algorithm address image that contains sky and ground as a part of the image. The ground acts as a support for segments (eg. Trees, buildings) in the image, thus a vertical image segments tends to have similar depth as its ground support. On the other hand, some images are not supported by the ground but they are connected to it, therefore these segments will have depth value larger than its nearest ground pixels.
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基于单眼图像的深度估计
本文研究了基于单目线索的深度估计。人类视觉系统使用单眼线索,如纹理、焦点和阴影来进行深度感知。我们提出的算法基于将图像分割成均匀的片段(超像素),然后从这些片段中提取地面段和天空段。这两个部分通过提供最大深度区域(天空)和最小深度区域(地面)来指导深度估计。片段的重置将在天空和地面之间有一个深度值。该算法处理包含天空和地面作为图像一部分的图像。地面作为支撑部分(如。树木,建筑物)在图像中,因此一个垂直的图像片段往往有类似的深度作为它的地面支撑。另一方面,有些图像不受地面支持,但它们与地面相连,因此这些片段的深度值将大于其最近的地面像素。
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