Advanced Techniques for Creating 3D Point Clouds: Using Stereo Vision in OpenCV Python
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Published 2021-09-21
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In this Computer Vision and OpenCV Video 📝 we are going to see How To Create Point Clouds with Stereo Vision in OpenCV Python. I'll provide the Python scripts with the images on my GitHub. You can just copy-paste everything and run it on your own computer. We will talk about stereo vision and how we can use it to create disparity maps that we can reproject out in the 3D world again. We will also take a look at the OpenCV documentation. At the end of the video, we will go through the code and create a point cloud and visualize it.
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Tags for the video:
#PointClouds #StereoVision #ComputerVision #OpenCV
All Comments (21)
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Hi thank you very much. What should i do if i want to use more than 2 cameras positions ? I use a robotic arm so i can take many pictures knowing the camera position each time.
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Very nice! What about a SLAM series? xD
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you are amazing my friend.!!
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Hi, do you know why I happen to have some coordinates in the .ply file with values as 'Inf' or '-Inf'? And if yes, do you know how to solve the problem? With those values i can not read the .ply file with open3D
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Could you tell me the kind of camera you are using as without a stereovision webcam I cannot run the code and I am not sure where to acquire one myself?
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Thank you man
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Hello, is it possible to get Q matrix from mononuclear camera?
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Hey everyone, just a quick one for anyone who need, in the video the two cameras are in a simple stereo setting- , no rotation only translation between two camera. Then, StereoRectify work fine. However if your stereo setting have each camera having rotation compared to the other, then you must use StereoRectifyUncalibrated otherwise it wont work well
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Really appreciate it so much, dude! @Nicolai. As you mentioned, comparably active method has higher precision for depth map, likewise the goal is to merge these stereo vision and one from the triangular-based approach, which is One shot structured Light. Is it possible to get greater precision than utilising solely stereo vision? If so, could you just give it a shot for us?
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Hello another great content! with the monocular camera videos you use deep learning algorithms to gain depth maps and say it's more accurate. If we use stereo camera without deep learning, dnn or ml will it be as accurate as monocular with deep learning or am I missing the videos of stereovision with deep learning?
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Nice
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Could you tell me what type of camera you are using and where I might acquire one as I cannot run the code properly with a monocular camera?
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Hi great video!! If I would like to make a real time 3d reconstruction using video stream instead of saved images do you think it’s possible with Open3D? I know it is similar to what is done in this video but i’m struggling with adding the new captured points to the previously created ply file and updating the visualization. Any help or guide is appreciated :). Thanks
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Do you also need a software to connect the two monocular webcams to create a stereovision?
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Which kind of lenses and sensor did you use for this case?
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how do i convert the point cloud to a grid to do path planning?
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Did you build this by connecting two webcams or did the webcam itself have two lenses? If so how did you build the camera?
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How can you get this Q matrix right I dont seem to be able to reconstruct using the reprojection matrix the output is mostly gibberish
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Hello, i have run the code provided on github using images captured by my own binocular camera system. However, I found that the point cloud generated contain a lot of infs, and the xyz coordinates are either extremely big or small. Can you give me some advice on why this could happen and how to solve it? Thanks in advance.
