Multiple cameras and motion detection on the Raspberry Pi
pyimagesearch.com
pyimagesearch.com
It is, however, expensive both computationally and storage (OPenCV is ~3 GB on it's own) so if you dont' need perfection there are other techniques that just compare entire frames rather than segmenting the frames.
Thanks so much for the kind words, and I'm happy the posts have helped! And as a fellow dog lover, it's awesome to see how you put together a real application for treat dispensing.
http://www.ivmech.com/magaza/en/development-modules-c-4/ivpo...
Claims to be able to do it "properly" - via the camera interface.
Later in the demo video, some of the frames are purple as it switches; it looks like invalid data for the end of the frame, and the Pi sync'ing to the output of the next camera when it starts transmitting its next frame.
I wonder if the commands for the module are covered in the MIPI docs, or if they just pass through anything the Pi sends. It seems like a cool device, and probably more practical for most people than the dual-CSI interfaces on the Pi Computer Module.
CSI is uni directional, camera is controller over separate interface (I2C)
dual csi on compute module is cool because you get four mipi lanes, and one of (former) broadcom engineers, 6by9, was kind and awesome enough to write _generic fully open source_ CSI driver, meaning you can use FPGA(for example MachXO2, lattice offers free MIPI cores) to pump up to 400 MB/s into Pee Linux userland
If you have any questions about computer vision, feel free to reach out!
What is the best way to read images from a DSLR attached to a Pi via USB?
I'd like to build a simple timelapse system where
- the image taking is done via the remote cable attached to GPIO pins of the PI
- each image, when taken, is sent to the Pi via USB (RAW+Jpeg) for processing, upload, etc.
The first part seems fairly easy, but the second part not so much. Any pointer appreciated.
If you knew the distance between each camera and triangulated plus a little math could speed be figured out?
Direct Linear Transformation is the standard way to do this using a control object (object of precisely known size and measurements) and cameras that don't move. Cameras film the object (usually a big cube), the object is removed, the cameras stay stationary, and anything that goes through that object's field of view can be tracked in all three dimensions. However, the cameras must not be co-linear and must be able to see a point on the object with both cameras, so this means no two front facing cameras, and realistically 4-5 cameras (though 3 can be done sometimes).
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