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| 2013-05-17 02:41:48 -0600 | asked a question | multiple object tracking using kalman filter As I know, kalman filter or camshift algorithm works well for single object tracking and prediction. For two or more ojects tracking, how can I use kalman filter to predict the positions? What is the state of the art multiple object tracking algorithm? Your suggesstions or comments are appreciated. Thanks. |
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| 2013-05-15 04:33:10 -0600 | commented question | How to speed up multiple object detection and tracking? Well, the requirement is 40 fps or more. The above steps would take more than 20ms... |
| 2013-05-15 04:29:51 -0600 | commented answer | How to speed up multiple object detection and tracking? Thanks for the detailed suggestions. The performance should be improved as per the above analysis. Yeah, the input are 3-channel RGB images. I'll update the sequences of these opencv steps. |
| 2013-05-14 02:00:57 -0600 | commented answer | How to speed up multiple object detection and tracking? The object is unregular finger points, I'm not sure whether the method works. Thanks a lot. |
| 2013-05-14 01:58:40 -0600 | commented question | How to speed up multiple object detection and tracking? It only told me the general rule for optimization. Any example code? |
| 2013-05-14 00:43:15 -0600 | commented answer | How to speed up multiple object detection and tracking? Thanks a lot for quick response. It looks like the answer what I'm looking for. Let me verify the method. Any suggestions for C language concurrency computing? |
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| 2013-05-13 22:08:03 -0600 | asked a question | How to speed up multiple object detection and tracking? Hi everyone. I have been working an moving object dection and tracking project. There're some questions that block me recently. Here are the opencv processing procedures: 0.Binary process 1. cvDilate 2. cvErode 3. cvCvtColor // CV_BGR2GRAY 4. cvSmooth 5. cvFindContours For an image with 360x60 pixels, it takes about 5ms to handle the above procedures, but it takes nearly 20 ms to process a picture with 1280x800 pixels. Since this is an real time project, 20 ms is unacceptable. I wonder if there's any improvement methods for it. The platform is VS2010+opencv 2.4.4+C language. I intended to adopt parallel processing like TBB or openMP, but don't know how. Besides, for multiple moving object detection and tracking, what is the best method? cvFindContours cant't find all the targets. Your suggestions are really appreciated. Thanks for the help in advance. Regards, Leon |