I am trying to perform dense reconstruction using a sequence of images from a calibrated stereo camera. I have been using orb-slam3 to give me the camera's pose estimation. I am also generating the disparity map and RGB point cloud given a stereo image pair using available ROS packages. Suppose my sequence of stereo images is circling around a computer desk. Now I thought since I have the pose of the camera, point clouds representing the same region of the scene from different view points of the camera should overlap; however, it does not seem to be the case. The point cloud of the same object is shifted around depending on the location of the camera. I was hoping to get something similar to this:

enter image description here

So I was wondering if there is a component I'm still missing? Is having pose estimation and point clouds from a camera enough to generate a dense 3d map or do I still need to apply an algorithm like ICP?


1 Answer 1


Small errors and outliers in camera poses will make the reconstruction unprecise, hence you need some refinement.

You have multiple options:


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.