采用几何复杂度的室外场景图像分割和深度生成

任艳楠; 刘琚; 元辉; 顾凌晨

doi:10.16798/j.issn.1003-0530.2018.05.004

采用几何复杂度的室外场景图像分割和深度生成

山东大学信息科学与工程学院

基金项目: 国家自然科学基金(61571274)；山东省重点研发计划(2017CXGC1504，2015ZDXX0801A01)；山东大学青年学者计划(2015WLJH39)；山东省自然科学杰出青年科学基金(JQ201614)；山东省自然科学基金(ZR2014FM012)

详细信息

中图分类号: TN911.73
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出版历程
- 收稿日期: 2017-10-25
- 修回日期: 2018-02-26
- 发布日期: 2018-05-24

Outdoor Image Segmentation and Depth Generation Based on Geometry Complexity

School of Information Science and Engineering, Shandong University

摘要

摘要: 本文提出一种采用几何复杂度的室外场景图像几何分割和深度生成算法。该算法首先通过图像中主要线段的角度统计分布将室外场景图像的几何结构规划为四种类型；然后，利用meanshift分割算法将输入图像分割成若干小区域，依据该图像的场景几何结构将这些小的区域逐步融合成为三个大的区域，每个区域具有一致的深度分布特点，由此实现输入图像的几何分割；最后，根据几何类型定义标准的深度图，结合输入图像的几何分割结果获得图像的深度图。实验结果表明可以通过简单的线段角度统计分布实现图像的几何分割，并进一步获得图像的深度图，与已有算法相比，提出的算法可以更好地保持深度图细节，更接近场景的真实的深度信息。
- 图像分割 /
- 深度图 /
- 几何 /
- 融合
Abstract: The paper presents an image segmentation and depth generation algorithm based on geometry complexity which is applied to outdoor scenes. Firstly, the angle statistical distribution of main lines in the input image is calculated and then the outdoor scenes are classified into four geometric categories. Secondly, the input image is divided into many small regions using the mean-shift segmentation algorithm, and then these regions are merged into three big regions based on the scene geometry category results. Each big region is in coherent depth distribution. Thirdly, a depth map can be generated based on the geometry segmented result and its standard depth map. Experimental results shows that proposed method can obtain an effective image geometric segmentation and meanwhile get a depth map with better details and more close to the true depth information of the scene.
- image segmentation /
- depth generation /
- geometric /
- fusion

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参考文献(18)

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