2D to 3D Conversion - Chevy Chase

It's time to do another 2d to 3d image conversion using Depth Map Automatic Generator 4 (DMAG4). To make it interesting, we are gonna look at the effect of increasing the number of scales. Recall that DMAG4 is based on Scale Space Random Walks (SSRW), which means that the number of scales used is at the heart of the method. In theory, a larger number of scales produces smoother depth maps but object boundaries might blur a little bit. When increasing the number of scales, it's pretty safe to reduce the number of iterations, if desired.

Original 2d image with the grayscale sparse depth map on top.

Depth map obtained by DMAG4 using Number of iterations = 3000 and Number of scales = 1.

Depth map obtained by DMAG4 using Number of iterations = 1000 and Number of scales = 3.

Here, I increased the number of scales by a factor of 3, so I reduced the number of iterations by the same factor (to save time).

Animated 3d gif obtained with Wiggle Maker.

It's interesting to see what Depth Map Automatic Generator 9 (DMAG9) can do on the exact same input (reference 2d image and sparse depth map).

Depth map obtained by DMAG9 using Sample spatial rate = 4 and Sample color rate = 32.

Depth map obtained by DMAG9 using Sample spatial rate = 8 and Sample color rate = 32.

Depth map obtained by DMAG9 using Sample spatial rate = 16 and Sample color rate = 32.

The depth maps produced by DMAG9 are quite similar to the ones produced by DMAG4 but DMAG9 is much faster than DMAG4.