Sorry I’m a bit late to a topic that I initiated. 
I didn’t know there’s single view depth prediction, amazing stuff.
Thank you so much to @hikinghack for pulling this together! Not to mention cross-posting this to the Wildlabs forum. Awesome to see a response from @Freaklabs there.
I just read this again, and think it might be helpful to think about this from the following angles.
0. Which ecological/conservation questions might depth-sensing data answer?
Some off the top of my head:
- Estimating wildlife populations - This is a big one, I know there are existing mathematical models that can make use of animal observation data only if there’s a good way to get depth-sensing info. Right now it’s a super labor intensive process that’s not practical (I can explain more if there’s interest).
- Measuring the size of animals - This can be a proxy for age, which provides demographic information about the species in question.
- Movement speed - If you can take images in burst mode (e.g. 3-4 photos per second) with depth data, you can estimate how fast an animal is moving.
- What else?
1. What ecological/conservation questions can each tech help answer?
For example, since structural light project is slow and can’t work on moving things, that constrains the type of data you get. Or, LIDAR scanners are powerful but expensive, so might be hard to deploy a large number of them in an array so you don’t get as much spatially distributed data. What are the implications of each?
2. Common evaluation criteria for each tech
Such as:
- Resolution
- Range
- Power needs
- Response time
- Spatial scalability (i.e. how feasible to deploy an array of these devices in the field)
- Cost $$$
- Can it sync with or replace existing camera trap images
- Technical complexity for building a camera trap out of it
How does the above sound? Is there a better approach? Or maybe I should post this to the Wildlabs forum instead. 
Eventually, I think it would be super cool to develop an open source hardware camera trap. But like @hikinghack said even the case would be a challenge, not to mention other things like a quick triggering system, power requirements, etc. But I think it’s a worthwhile endeavor especially if we can bring new technology to the table like depth-sensing, something multiple ecologists have dreamed about but don’t have the ability to create.
Maybe a first step is to see if @Freaklab’s BoomBox system can be adapted??
I know @laola has also indicated an interest in this, so please chime in!