I have never ever asked this kind of question on StackOverflow before, and I wonder if you could help me guys because it is a "bit" vague.
I have to design a project that uses Teensy (simple ARM platform) for getting data from IR camera (Flir, resolution 80x60) over SPI, and streaming these data to Linux/Windows running machine (through USB-serial) and doing something simple with OpenCV.
THE PROBLEM: The project lacks some "inovation". It should not be something very complicated, but rather different approach, or trying something new.
Do you have recommendations/tutorials/books/experience with working with above mentioned things? OR do you see a potential for teying something new?
You might want to check out the OpenCV Cookbook for some ideas.
There is a project using this FLIR with a Teensy. It provides a thermal image using a small LCD screen (without any aditional computer).
https://hackaday.io/project/8994-diy-thermocam
So, the teensy can get data through spi.
Can the teensy send data through usb then ? Probably but you will have to check if the rate is high enough
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Using OpenCV directly on teensy is not possible because of size of library. But you can probably make some basic image processing if the code is small enough.
The FLIR Lepton can be directly interfaced with Linux or Windows computer, so I don't really see the use of Teensy.
I would recommend a Raspberry Pi to interface the FLIR Lepton and then do some image processing. It's well documented on the web.
Related
i want to do a project which uses eye tracking, is it possible to port an open cv code on a microcontroller.
i am new to opencv as well as microcontroller so can any one tell me if it is possible to make a code which works like this vedio.
http://www.youtube.com/watch?feature=endscreen&v=eBtpKAja-m0&NR=1
Q: Can i use an eye detecting opencv code on microcontroller?
A: Yes, you can
Q: Is it possible to port an open cv code on a microcontroller
A: OpenCV is already in the Unix and Android platform. The easiest approach therefore will be to get hold of some embedded device with ARM. There are a lot of help available for the 'OpenCV-ARM' combination.
Beagleboard and RasberryPi are the cheapest embedded ARM devices available for less than $150. Sometimes they come preloaded with Unix boot system and opencv2.0. Thus it would be so easy to run the executable that you created in the computer system.
Be aware of the speed of the processor. If your algorithm is computationally intensive then you wont be quiet satisfied with the output being obtained in the low-end embedded devices.
If some ARM embedded Linux board can fit into your definition of microcontroller, then there is nothing to port.
http://www.google.com/search?q=opencv+arm
I'm new to embedded software, I want to build a Image processing application for my AT91SAM9261-EK development board by Atmel. To make it simple i want to use the OpenCV functions, but i'm not sure how am I going to generate a .bim file for flashing on the brd.
Also can anyone you help me understand the flow / software structure for these kind of applications?
Like, will I need Linux or any other OS, if so where does the actual image processing code which i intend to write using opencv sit ?
Till now for simple codes like Basic LCD project, for this board i'm compiling the code using IAR workbench, so if I want to use the same for opencv functions, is there a way ?
Is there any other open source image processing libraries similar to opencv & easy to integrate with IAR or any other ARM compiler ?
Also it would be really useful if there are any links to some learning documents regarding this
Thanks in advance ?
Depending on your application, I think that CPU is not going to be powerful enough to do any kind of image processing; plus the weirdness of working with a foreign system is not going to make your life any easier.
If using this exact CPU is not super important I'd recommend a Beagleboard or Pandaboard, mainly because Ubuntu has installers targeted to the boards and Ubuntu/Debian offers OpenCV packages out of the box, and this is going to remove a whole lot of hurdles if you're new to embedded development -- basically it turns your dev board into a full-featured computer, just plug in a monitor, keyboard and mouse.
The Raspberry Pi looks to be promising in this regard as well, and you certainly can't argue with the price! (You may be able to install Debian on your board and get access to OpenCV packages this way, but I can't vouch for the ease-of-use of this method compared to Ubuntu, which is difficult enough, especially if you're new to Linux).
I'm searching for a face tracking system to use in an augmented reality project. I'm trying to find an open source and multi-platform application for it. The goal is to return the direction where the face is looking to interact with the virtual environment, (something like this video).
I've downloaded the sources of the above Johnny Lee's application and tried to use Free Track too, making my own headset (some kind of monster, hehe). But it's not good to be limited to infrared points in your head.
These days I've download FaceTrackNoIR, but when I launch the program I get "No DLL was found in the Waterfall procedure." that I'm actually trying to solve.
Anyone knows a good application, library, code, lecture, anything that could help me to find a good path for this?
Thank you all!
I'll try to post results someday :-)
I would take a look at OpenCV. It is a general purpose machine-learning and computer vision C++ library. One of the examples in the download is a real-time face tracker that connects to a video camera connected to your computer and draws squares around any faces in the camera view.
I'm writing LabVIEW software that grabs images from an IMAQ compatible GigE camera.
The problem: This is a collaborative project, so I only have intermittent access to the actual camera.I'd like to be able to keep developing this software even when the camera isn't present.
Is there a simple/fast way to create a virtual or dummy IMAQ camera in software? Ideally I'd like the dummy camera grab frames from an AVI or a stack of JPEG's. Something like this must exist, I just can't find it on Google.
I'm looking for something that won't take very long (e.g.< 2 hours effort) and that is abstracted away through the standard LabVIEW IMAQ interface, so that my software won't know or care whether its dealing with a dummy camera or an actual camera.
You can try this method using LabVIEW classes:
Hardware Emulation Using LabVIEW Classes
If you have the IMAQdx driver, you might consider just buying a cheap USB webcam for $10.
Use the IMAQdx driver (assuming you have it), and then insert the Vision Acquisition Express VI, and you can choose AVIs or even pics as a source.
Something like this: GigESim is a camera emulation software. Unfortunately it is proprietary and too expensive (>$500) for my own needs, but perhaps others will find this link useful.
Anyone know of a viable Open Source alternative?
There's an IP Camera emulator project that emulates IP camera with python. I haven't used it myself so i don't know if it can be used by IMAQ.
Let us know if it's good for you.
I know this question is really old, but hopefully this answer helps someone out.
IMAQdx also works with Windows DirectShow devices. While normally these are actual physical capture devices (think USB Webcams), there is no necessity that they have to be.
There are a few different pre-made options available on the web. I found using Open Broadcaster Studio and this Virtual Cam plugin to be easy enough. Basically:
Download and install both.
Load your media sources in the sources list.
Enable the VirtualCam stream (Tools > VirtualCam). Press Start.
I am starting to develop an automated webcam application. The goal is to automatically take pictures, do some image processing and then upload the results to a FTP site. All of these tasks seem simple.
However, I am having a hard time to find a decent camera. I don't want to use a simple webcam or hd-webcam because the image quality of still frames isn't very good.
I'm also having a hard time finding an affordable digital camera supporting USB snapshot or control.
My second concern is the development itself. I'm not quite sure which programming language to use. I have experience with AS3, Processing, Java and some simple C++ and Open CV.
Do you have a clue?
Regarding the camera, There are pretty good webcams that you can find, some with HD quality. look at the cameras on Logitech (I tested their API and it is quite good), A HD camera has a retail of $99 which is very cheap. If you are looking for something better I would go with Nikon as they also have a pretty good API for C#/C++. You can get a basic SLR with simple 28mm lens for $500. Don't use a PowerShot as Nikon stopped supporting their API. Whatever camera you decide to buy make sure a proper API is available, is being maintained and free.
Regarding development, I would go with C#/Java as they are easier than C++. There are quite allot of libraries for image processing for C#/Java, just make sure that the Camera comes with an API the fits your chosen language.
Good luck.
Generally (from experience) most USB cameras that show up as an imaging device through Windows can be used with JAI [Java Advanced Imaging]. Additionally [on the .net/c++ side], the same cameras can be used through DirectShow as a capture device. Java/C# will make development easier but expect to loose some performance [even with the best of optimizations]. Additionally you can only perform upto the speed of the camera and the data line running from the camera to the computer [USB1.0 will seriously limit a decent framerate]
first get the image in RAM:
If you are using CHDK, I suggest you get the image copied from camera memory to RAM by using supported scripting languages by CHDK - you can take help from the CHDK forum http://chdk.setepontos.com/index.php for this.
or if thats difficult you can continuously copy the image to hard disk and load in RAM from there. (you need to take care (delete) of massive images accumulated on hard disk in a short period of time !)
This sounds like a 'brute force' approach, but will get your work going while you are researching correct approach.
perform image processing:
once the image is in RAM, you can apply your image processing algorithms as usual e.g. using opencv library.
hope this helps you