Show Posts

This section allows you to view all posts made by this member. Note that you can only see posts made in areas you currently have access to.

Messages - Karma Lies

Pages: [1]
Academic Corner / Depth map generation using focus stacking
« on: December 17, 2019, 08:36:14 AM »
Hi! This is my first post, but I've been a longtime user of ML. I just graduated from Purdue with a degree in computer science, where I researched the concept of generating depth maps for a scene using a DSLR. My vision is to be able to take an input stack of images as DNGs which are then processed into a single, all-in-focus DNG with an embedded depth map. That could open up the creative post-processing potential for focus stacks in RAW editors like Photoshop/Lightroom since those programs already support the use of embedded depth masks.

At the project's current state, there's quite a bit of room for improvement in polishing up the generated depth maps. Although, just a few improvements (i.e. image segmentation, Homography/ECC alignment) to the core pipeline of the project could improve the quality of these depth maps to near perfection. The algorithm is currently fed by JPEG inputs for ease of fleshing out the core of the program, but I want to eventually integrate DNG processing for the above reasons.

The work I've done so far is standalone to ML, but I would be interested in involving my project in some ML development (if deemed justifiable or necessary beyond the current focus stacking module).

Down the road, I would even like to integrate depth by defocus algorithms to generate a depth map from 2 or 3 shallow depth-of-field shots. That would unlock some potentially game-changing portrait post-processing capabilities.

Feel free to check out the project's GitHub repository:

I would love some more contributors in manifesting this vision. To my knowledge, I haven't seen any other open source projects like this for creatives -- only a couple proprietary depth-map generators and then some algorithms described in academic papers without any source code.

Pages: [1]