I want to capture a specific ROI (say 20x1800 region) of raspberry pi camera. First, I used the raspistill --roi. It gave me a zoomed image. The same happend with picamera crop method. So I decided to capture the whole image by raspicam and then using OpenCV to crop the image. It gave me a 20-27 frames per second. Isn't there any faster solution?
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The datasheet of the OV2640 camera mentions the possibility to mirror or flip the image (see "REG04"). For my application it is, however, crucial to know the location of each pixel. Since the camera also crops the 1632x1232 sensor to a smaller, e.g., 1600x1200 image, the order of operations is important.
So does the camera first crop the image to the 1600x1200 window and mirror/flip it afterwards, or does the mirror/flip happen before the windowing?
I'm fairly new to computer vision and currently trying to make the following happen, but had no success so far.
My situation: I want to track different landmarks of a person with mediapipe. Tracking with a single camera works fine and also tracking with two cameras at the same time. What I want is to receive the same coordinate from each camera for a point that has been detected. For example: Camera 1 found the landmark of the left shoulder with the x and y coordinates (1,2). For camera 2 the same landmark has obviously different coordinates lets say (2,3). Ideally there is a way to map or transform the coordinates of camera 2 to camera 1.
the following picture shows the camera setup
Camera setup (I can't post images yet)
So far I've tried to use stereo camera calibration as described here: https://temugeb.github.io/opencv/python/2021/02/02/stereo-camera-calibration-and-triangulation.html. But this doesn't seem to do the trick. I receive a rotation and translation matrix as an output from the calibration, but when I concatenate them to a transformation matrix and multiply it with the coordinates of camera 2, the results don't match with the coordinates of camera 1.
I've also tried to implement planar homography, but since the observed scene isn't limited to a plane, it isn't working well.
The idea behind this is to increase to probability that the landmarks will be detected and use both camera streams to build a full set of coordinates for all desired landmarks.
Is it possible to do what I want to do? If so, what's the name of this process?
I'm really grateful for any help. Thanks in advance.
I am creating a 3d text on blender2.8 but I am having a hard time trying to make it appear on the camera view.
I have tried rotating and scaling the camera but it doesn't help.
The camera object is the focal point for the final image, like in real life, if you want to get more in the picture you need to move the camera back or zoom out.
With the camera close -
With the camera far away -
To zoom out, you reduce the camera's focal length.
Kinect camera has a very low resolution RGB image. I want to use point cloud from the depth kinect but want to texture map it with another image taken from another camera.
Could anyone please guide me how to do that?
See the Kinect Calibration Toolbox, v2.0 http://sourceforge.net/projects/kinectcalib/files/v2.0/
2012-02-09 - v2.0 - Major update. Added new disparity distortion model and simultaneous calibration of external RGB camera.
I am writing a Cocoa application for mac osx. I'm trying to figure out how to determine the size of an image that will be captured by a camera? I would like to know the size of the image that will be captured so I can setup a view with an aspect ratio that won't distort the image. For example, if my view is defined to be 640x360 and my camera captures images that are 640x480, the displayed image looks short and fat. I'm also displaying some other layers over the image and I need the image size to be able to scale and position the layers properly.
I won't know the type of camera that is attached until run-time so I'd like to be able to interrogate the device and get attributes like image size. Thanks for the help...
You are altering the aspect ratio of the image when you capture in 640x360 instead of 640x480 or 320x240. You are doing something similar as a resize, using the whole image and making it a different size.
If you don't want to distort the image, but use only a portion of it you need to do a crop. Some hardware support cropping, others don't and you have to do it in software. Cropping is using only portions of the original image. In your case, you would discard the bottom 120 lines.
Example (from here):
The blue rectangle is the natural, or original image and the red is a crop of it.