Compute a free space/obstacle mask for an image (pixels) for pixel-level image segmentation
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caesar
am 19 Okt. 2018
Kommentiert: caesar
am 19 Okt. 2018
I am working with pixel-level image segmentation in Matlab. I am trying to build a model to classify each pixel in the RGB image either Free space (F) or Obstacle. If the pixel is belonging to an object outside a threshold distance from the camera location then it is free otherwise its an obstacle. The main challenge I have now is labeling the data set. Is there any way I can come up with an algorithm in Matlab that will do the labeling process automatically, apart from image labeler app, i.e compute a mask of (F)/(o) for the image?. Assuming that I have a synthetic 3d environment to collect images from by changing the position and orientation of the camera within the environment. So known things are :
1-Camera properties (focal length, sensor size,..etc)
2-Camera location within the environment (X, Y, Z)
3- Objects' location and dimensions.
please advise me if you have any suggestion.
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Image Analyst
am 19 Okt. 2018
I don't know how you know if a pixel is free space or not - maybe the color, maybe spatial information from neighboring pixels also? Maybe it's the pixel brightness or color or texture in an immediate neighborhood. But whatever it is, you have to get an image that has the probability (percentage) that each pixel is either obstacle or free space. Then you can simply threshold that.
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Image Analyst
am 19 Okt. 2018
I thought that since you were ready to do the labeling that you had it already. If you don't, see the camera calibration capabilities of the Computer Vision System Toolbox: https://www.mathworks.com/products/computer-vision/features.html#camera-calibration
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