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OpenCV 4.5 simple optical flow GPU tutorial cuda::FarnebackOpticalFlow

This OpenCV tutorial is a very simple code example of GPU Cuda optical flow in OpenCV written in c++. The configuration of the project, code, and explanation are included for farneback Optical Flow method. Farneback algorithm is a dense method that is used to process all the pixels in the given image. The dense methods are slower but more accurate as all the pixels of the image are processed. In the following example, I am displaying just a few pixes based on a grid. I am not displaying all the pixes. In the opposite to dense method the sparse method like Lucas Kanade using just a selected subset of pixels. They are faster. Both methods have specific applications. Lucas-Kanade is widely used in tracking. The farneback can be used for the analysis of more complex movement in image scene and furder segmentation based on these changes. As dense methods are slightly slower, the GPU and Cuda implementation can lead to great performance improvements to calculate optical flow for all pixels o
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Opencv head and people detection code cascade

 head and people detection Opencv LBP CascadeClassifier 



This LBP cascade for opencv will be available soon. People is just new version of the old one published here. Head detection is new one. Just trained.

LBP cascade description

I trained cascade just on hopefully well selected 2000 positive images and 2400 negative. Great effect has also selection of the negative samples. I need to find more about this. Same positive samples and different negative set of samples should lead to big different kind cascade property. Yes positive samples is good to have somehow unique (situation, positive, background, rotation etc). The negative samples are simple to capture. Random crop from the several pictures from vacation. Nothing special. But there is also the magic behind. Instead of try different kind of positive samples. Try the negative. Easy to collect and performance of the cascade should be rapidly different. Also, It is not necessary to have 100 percent clear negative sample. If there is 1 positive inside the negative set. Maybe more. It is not necessary something wrong. More details after release.... Soon hopefully

 



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  1. UnknownJanuary 2, 2017 at 2:25 AM

    Hello,
    The Article on Example LBP CascadeClassifier for head and people detection is nice.It nice to know the detail information.Thanks for Sharing the information about it.internet of things services

    ReplyDelete
    Replies
    1. VlJanuary 10, 2017 at 11:34 AM

      Cascade is available to download.. Share my page instead of yours. :D Thanks

      Delete
    2. CamilleMay 3, 2017 at 7:31 AM

      Where is the link ?

      Delete
  2. UnknownJune 6, 2017 at 11:51 AM

    Is there a classifier to detect heads from the top where faces may not be visible? If i have my camera on top of my door? face may not be available but the head? any suggestions on what would be the best classifier in that case?

    Thanks.

    ReplyDelete
  3. amulet88November 9, 2019 at 11:07 PM

    Thank you for sharing information. บาคาร่าออนไลน์ ดีที่สุด

    ReplyDelete

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