The one new looking item is the VisionBonnet (with a low power Intel Movidius chip [1]). I've been pounding away on a low power / low cost NN vision device and now in the last two days we got Amazon DeepLens and this Google AIY Vision kit. Exciting and frustrating at the same time.
I'll go with exciting. I'm looking at doing some computer vision (at least background segmentation for motion detection) as part of a security camera NVR project. I was eyeing the Hexagon DSP 680 included in the newest Qualcomm SoCs but couldn't find a cheap SBC that included it. At first glance, the VisionBonnet seems to do similar things as part of a $45 kit. As a bonus, they say it's supported by TensorFlow. That will be helpful if I ever actually get into machine learning...
On second glance, I think it's a pretty different device than the Hexagon DSP 680 I mentioned.
For one thing, this board in particular apparently has a direct connection to the camera. I'm not sure if you can do anything but live video from the directly-connected camera (in my case, I want prerecorded video / video from IP cameras). Maybe it can but it's not immediately obvious anyway.
The $75 "Movidius Neural Compute Stick" uses the same chip and does everything via USB so that's more promising. But it's a binary-only API that's totally focused on neural networks (and only available for Ubuntu/x86_64 and Raspbian/arm7). In contrast, I believe you can easily send Hexagon arbitrary code. Its assembly format is documented and upstream llvm appears to support it. So if I want to do background subtraction via more old-school approaches, the Hexagon is probably useful where the Movidius stuff is not. And I have yet to learn anything about neural networks so that's a significant factor for me at least.
Really neat hardware but I wish it were more open.
If I was going to do some embedded image processing I would choose a Tegra. You can get a Shield TV for not too much money, and although I haven't done it myself it looks pretty hackable with both Android and Ubuntu (and if you don't want to hack it you can just buy the devkit). CUDA is a decent toolkit and of course NVIDIA's support for neural networks is by far better than anyone else's.
