How to do Stereo Vision and Depth Estimation with OpenCV C++ and Python

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In this video 📝 I'll talk about Stereo Vision and Multi-View Camera Geometry. We will first talk about the basics of stereo vision and multi-view camera geometry and how it can be used to estimate depth in an image or in a camera. We can then operate with 3D images instead of only 2D with one camera. This can be combined with an obstacle detection algorithm as well, and we can get a position of the detected obstacle and the distance to it. We will in this video see what the different steps are and go over a practical example as well.

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Tags:
#StereoVision #SteroeCamera #DepthEstimation #ComputerVision #ObjectDetection #DistanceEstimation #OpenCV #MultiViewGeometry
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Enroll in My School and Technical Courses

NicolaiAI
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Last week I received an OAK D kit and then today I got to know about your channel (best combination videos are so awesome....I instantly subscribed and became a big fan of your work....keep shining

nilutpolkashyap
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Thanks a lot, this is the best video I've seen about all the process of a simple stereovision system.

hamzaomari
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Thanks a lot for explaining stereo projection in simple words rather than math and vectors :D (most computer vision books do)
I wanted to ask, if the cameras were placed in orthogonal positions and not in same axis, can we apply the same formulas and techniques to find the depth estimation and corresponding 3D reconstruction to get 3D coordinates of an obstacle/detected object?
Thanks in advance!

raihankhan
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Please make a video on deep learning based depth estimation works. Thanks

SAINIVEDH
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HI can you combine both Camera Calibration and depth estimation as a single vedio? That would be greate if you do so ..

janaeshkrish
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How the aggregate cost computation algorithm ?

omarmurajia
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Thank you for this interesting video. What do you think about the approaches to use neural networks to compute depth from stereo pair images? Supposedly they're faster, but it would be interesting to hear what a pro thinks about it

fiNitEarth
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Hi, I recently explored some deep learning approaches for stereo and I am very new to it. Can you please help me by telling what’s the difference between stereo matching networks like GANet and stereo depth estimation networks like MVSnet. Thanks

satishsinha
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I'm planning to use a single camera to detect various points of interest such as banks and pharmacies (specifically, to detect their logos). I have already trained a YOLOv8 model for this purpose and aim to calculate their 3D coordinates . Can YOU help me with a code that can calculate the 3D coordinates of detected objects in the image using a single camera? I'm considering treating two consecutive images from the camera as if they were captured by two separate cameras, thereby making stereo vision applicable. Additionally, the coordinates of the camera are always known via GPS

BlueWolf-ryos
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do you know, what kind of metrics or procedures autonomous car use to detect obstacles and the distance to the obstacles?

schnebastian
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Love this tutorial.
Is it possible for you to share the code? Because the link you mentioned here does not refer to any page or repository on Github.

salmansaleem
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Thank you for a very informative video! I have written a program that already gives me the position of the object that I want to track, so I already got its x-coordinates from both cameras. Is it then necessary to create a disparity map of the whole frame in view or is it enough to just calculate the disparity of my one target point?

faizaali
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Isit possible to get a pdf copy of the notes you shared in this video? so that i can refer to it for my project

nigellim
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I want to get the steroe camera, but I don't know what type or version was used in the video. Can you help me?

fairozashour
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I am bit confused with stereo vison approch and Structure from motion (Photogrammetry approach)

Bala
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Hey Nicolai. What is a decent sterovision camera (maybe with usb) for a decent price atm?

QuarktaschemitSenf
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i am immature in this what you mean by depth of the image...i didn't clearly

souravsahoo