Depth estimation from a monocular view of the outdoors

This study presents an algorithm for estimating three-dimensional (3D) depth from a single monocular outdoor image. This algorithm combines three major components: the initial depth prior, the dark channel prior, and multi-resolution analysis. The initial depth prior assigns an initial depth to each object based on its location in the image. The object segmentation in this step is based on edge, hue, and saturation. The dark channel prior cooperates with color saturation to generate approximate depth information. Combining the depth maps of both initial depth prior and dark channel prior generates depth maps of three resolutions. Fusing these maps together across different resolutions produces the final depth map. Experimental results show that the proposed method achieves a considerable computational savings compared to existing methods while retaining a depth map close to the ground truth.