Outdoor Image Segmentation and Depth Generation Based on Geometry Complexity

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.