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Algorithms for Motion Tracking?

Posted by Cliff on from the complex-image-recognition dept.

Keith Handy asks: "I seem to be unable to find algorithms and/or open source programs that will do accurate motion tracking, i.e. you mark a point on an object in frame 36, and the program can follow that point on that object through all the frames following it. This is useful not just for analyzing motion, but also for interpolating/extrapolating frames of video -- so if you had something at only 15 fps, you could generate inbetween frames (which are not just crossfades between the frames) and actually smooth the effect of the motion. Not something so complicated as to get into actual physics -- just something that will indicate where (in 2D only) that part of the object has moved from one frame to the next, for any given point in the whole picture. And for that matter it doesn't have to be 100% accurate, just any means of generating a reasonable motion-flow map." This doesn't strike me as an easy algorithm to develop, but are there any papers online or offline, that might describe an algorithm that can at least track objects in an image?

"In other words, I want something that does this, in order to write code that will do things like this and this. I already know how to write code to blur and warp images, so to be able to track motion would give me (and you) the same capabilities as these expensive plug-ins.

Anyone know any other resources, directions, or existing code I could look into to find out more about how this works, so I can incorporate it into my own programming instead of paying hundreds or thousands of dollars for limited, proprietary use of the technology?"

6 of 32 comments (clear)

  1. Book by rm-r · · Score: 5, Informative

    Hmm, not sure about any resources on the net, but I did similar stuff at uni so I can recommend a book. Try Image processing, analysis and machine vision by hlavac et al. It's a very good book with plenty of code-neutral algorithms. Good luck.

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  2. Video compression by cperciva · · Score: 3, Informative

    I think the best use of this would be in video compression -- if you can recognize the movement of objects between frames, you can encode how much things have moved instead of re-encoding the entire image.

    Which is exactly what MPEG does... very crudely. The MPEG solution seems to be to compare a block (8x8?) of pixels with every block in the previous frame.

    The fact that MPEG doesn't use anything more sophisticated than this suggests to me that there probably aren't any algorithms which consistently work better.

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    1. Re:Video compression by rm-r · · Score: 2, Informative

      Motion tracking is also useful in military software, ie to find that pesky moving Afghan and point a gun at him. Similar technology is also used in some CCTV systems, but apart from that it doesn't seem to have crossed over into the mainstream much. There's a lot of cool software and ideas out there, much of it in the public domain if not GPL'd exactly so I'm sure it's just waiting for someone with a really good idea...

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  3. openCV by bjpirt · · Score: 5, Informative

    have a look at openCV (stands for open computer vision), it was originally developed by intel, but was later open souced. runs on both linux and windows and is mainly used for real time motion tracking of live video sources. i'm sure there are some pretty nice algorithms in the source there somewhere. They have their stuff on sourceforge

    and a yahoo groups support forum thing here

    the original intel pages are here
    cheers,
    bjpirt

  4. KLT Feature Tracker by The+Whinger · · Score: 5, Informative

    Have a look at the KLT tracker - that will probably do what you want.

    An implementation can be found here:

    http://vision.stanford.edu/~birch/klt/

  5. just use the MPEG algorithm by dutky · · Score: 4, Informative
    Other folk have mentioned the MPEG motion compensation algorithm (though I think they got it a bit wrong). The algorithm chops up the current frame into 8x8 pixel block on even block sized boundries (first block at (0,0):(7,7), second block at (0,8):(7,15), and so on). These blocks are then compared against all possible 8x8 pixel blocks, local to the original block, in the adjacent frame (we compare against the blocks shifted by 1, 2, 3, 4, 5, 6, 7, and 8 pixels in both the x and y directions). Essentially, each block is compared against every possible sub block of a 12x12 pixel block centered on the original block's position. The comparisson succeeds if the difference between the two blocks in small enough (this is a threshold that you set).

    Once you have done this for every block in the original frame, you have a set of motion vectors from which you can construct an intermediate frame.