On Thu, Apr 18, 2013 at 8:42 AM, Antoine Villeret <antoine.villeret@gmail.com> wrote:

i tried CCV one time but i had some driver and performance issues
moreover, i can't find an easy way to tune the processing chain

pd is more flexible but, i agree, could be harder

--
do it yourself
http://antoine.villeret.free.fr

2013/4/18 John Harrison <john.harrison@alum.mit.edu>
I'm not totally clear on the big picture here but it could be you might save yourself a lot of time and effort doing your blob tracking with Community Core Vision (CCV) then sending the blob data to Pd through OSC. After initially doing my blob tracking in Pd only (which did work), I switched to this CCV --> Pd approach and got better results because of all of the built-in filtering etc. that is provided with that open-source cross-platform software.

-John

On Thu, Apr 18, 2013 at 5:22 AM, Ska Frenz <skafrenz@gmail.com> wrote:

Hi, thank you for the suggestions, I'll check openCv. Can you explain how to use "morphological filters" to clear up the noise in the image? Are there examples around? Also, could you please explain me better what do you mean with "adaptive background subtraction method"?

Thank you for your time :)

francesco

2013/4/17 Antoine Villeret <antoine.villeret@gmail.com>

hi,

the segmentation method (how you extract what is your interest from the rest of the image) is very critical in video tracking

background subtraction is a basic way to extract blob and it works only in certain conditions of light (if you want to track something outdoor, you should use an adaptive background subtraction method)

moreover, there is no general method to do video tracking, it depends on what you want to track and how it is filmed

so, the first thing is to have a good image, with not too much lighting changes, good contrast between background and features to track

then you can start thinking about segmentation, and the segmentation accuracy depends on the quality of the video
you may need to do something more than just background subtraction, for example, you could apply some morphological filter to remove noise

after that, you can start tracking
you could also apply a threshold on the blob size to not track very small blob
blob of interest are often surrounded by very small blobs due to segmentation noise

but you can have a look at pix_opencv objects,
there is [pix_opencv_blobtrack] which implements a whole processing chain, including foreground extractor, blob detector, blob tracker and follower

I'm not sure it's included in pd-extended, but you can find some binaries on build server

hope this help

antoine

--
do it yourself
http://antoine.villeret.free.fr

2013/4/17 Ska Frenz <skafrenz@gmail.com>

Hi everyone, this is my first time on the pd-list so I hope I won't do anything wrong.
I'm writing here to get some help about pd tracking objects (pix_blob..). I'm using the background subtraction method, to track objects and I need help to understand how I can track multiple objects with multiples different blobs. I'm trying the pix_multiblob and yes, it show 2 blobs..but they track the same object. Then basically I do not understand how can I make the first blob to follow just one object for all the time that specific object is inside the webcam rectangle, and the second blob to track another separate object. I cannot find any material that clearly talks about this.I attached the patch I'm working on. I'd love to see some well-explained examples if you know where to get them.

Thank you very much for your help :)

Francesco

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