Compute a free space/obstacle mask for an image (pixels) for pixel-level image segmentation
1 visualización (últimos 30 días)
Mostrar comentarios más antiguos
caesar
el 19 de Oct. de 2018
Comentada: caesar
el 19 de Oct. de 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.
0 comentarios
Respuesta aceptada
Image Analyst
el 19 de Oct. de 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.
5 comentarios
Image Analyst
el 19 de Oct. de 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
Más respuestas (0)
Ver también
Categorías
Más información sobre Computer Vision with Simulink en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!