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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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Computer vision IOT company PointGrab Raises $5M

IOT computer vision

Computer vision IOT company raises $5M from Swiss fund ABB Technology Ventures, EcoMachines Ventures in London, and Silicon Valley-based Flex Lab IX.


This home automation company develop application for daily usage.

pointgrab

 Features of Pointgrab Intelligent Optical Analytics

 • People counting, Location and Tracking
 • Accurate and reliable detection of human presence
 • Screening out regions of no interest (using digital masking) Light sensing
 • Highly accurate average Lux reading (globally and in selective zones)
 • Color temperature measurement

This company is trying to focus on 3 major segments of today. Frist is internet of things, second big data and machine learning.

 Great idea of Pointgrab  project

Save energy:
This could be based on detection of lighted lights and presence of people in room. In case, People are no longer in room algorithm could make a decision to switch the lights off. This technology can also make a decision like, You are going sit into a chair lets switch main lighting of the room off and turn on small lamp close to you.
This is some of great example how this technology could save the many.

The only problem that I see here is false detections that could switch light on or call security agency in wrong time. The algorithm could works perfectly for 99 percentage time of the day but wrong alerts are problem in many situations.

Another advantages is image processing on sensor level. Tracking and location on sensor level could be anonymous enough for most of us.


Point touch

Another great product is Point Touch, which is gesture controls for customer devices. Experience in this area say that the mouse and keyboards are more comfortable than waving hands. But in some situations this could be supplement of standard interface for example in smart panel in shopping centers, where the motivation is simple. Someone does not want to touch what everyone else.


 
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Comments

  1. Linktekc Systems GroupMarch 3, 2018 at 9:14 AM

    I am thankful for this blog to gave me much knowledge regarding my area of work. I also want to make some addition on this platform which must be in knowledge of people who really in need. Thanks. Face recognition Mobile apps

    ReplyDelete
  2. UnknownSeptember 28, 2018 at 5:01 AM

    Nice and good article. It is very useful for me to learn and understand easily. Thanks for sharing your valuable information and time. Please keep updating IOT online training

    ReplyDelete
  3. thanidaNovember 27, 2018 at 8:03 PM

    I saw this post. You are really great. Keep Up the Good Work man.
    ufabet

    ReplyDelete

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