How to generate a 3D point cloud from a depth image?

How to generate a 3D point cloud from a depth image?

I am trying to convert a depth image (RGBD) into a 3d point cloud. The solution I am currently using is taken from this post where: The depth measurements have been taken from a pin hole camera and the point cloud is projecting away from the centre (example images below). Can anyone help me understand why and how I can solve this?

What can you do with a depth map?

According to the Wikipedia article about it: A depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. This information can be employed in a wide variety of applications in the fields of image processing, mapping, navigation and many others.

How to convert a RGBD image to point cloud?

In the code (cₓ, cᵧ) is the centre of the camera sensor. Note the constant pxToMetre, a camera property, which you can determine if the focal length is known both in units of meters and in pixels. Even without it, the picture is accurately represented in 3D up to a scale factor. Of course there is a more general way to do all this.

How is the distance of an object calculated in a depth map?

The distance (orthogonal to the axis) from the object (a red dot in the figure) to the camera’s sensor is the one that is stored as a pixel value in the depth map. Obtaining the x coordinate of said sample means to calculate the horizontal distance between the object and the center of the sensor. This can be done with:

How to convert a depth map into a 3D scene?

Since it is an upper triangular matrix there is an easy analytical solution: Eq 7: Inverse o f K with all components. Now you have all the tools at hand to convert a depth map or RGBD image into a 3D scene where each pixel represents one point (Fig. 3).

How is each pixel assigned a depth and colour?

Each pixel has a colour and a depth assigned. (right) 3D view in cartesian coordinates x, y, z. It is important to know your camera’s properties if you want to understand what each pixel corresponds to in a 3D environment.