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Color 3D Point Clouds with Basler blaze

The spatial depth data from the Basler blaze 3D camera can be merged with the RGB data from a color camera, such as the Basler ace. The result is a colored point cloud (RGB-D for short) in which each 3D point is assigned a color value. In fact, our human brain also combines the disparity information between the views of our two eyes with color information and prior knowledge about the detected objects to obtain the scene structure.

3D point cloud in true RGB colors

If the depth values of the Basler blaze camera and the additionally captured color values of an RGB camera are merged, point clouds can be displayed in the objects’ true colors. This can help to compensate for missing depth information, to perform classifications additionally based on object color, or to simplify scene understanding.

First image
Second image

3D point cloud in false colors

The Basler blaze camera provides 3D data as a range map or point cloud. A point cloud contains the x,y,z 3D coordinates for each sensor pixel. For user-friendly evaluation, the points are often displayed in rainbow colors (rainbow color mapping). Depth values in the near range appear red to yellow, distant values green to blue.

Would you like to learn more about this solution?

Would you like to learn more about this solution?

Our Application Note „Merging Color Data of Basler 2D Cameras with Basler blaze Depth Data“ explains how by combining a 3D camera with a color camera, depth values can be displayed in true RGB colors.

Download Application Note

Advantages of RGB-D: When does the combined use make sense?

Robust object detection and classification with increased accuracy of correct matches, especially for similarly shaped objects

Robust object detection and classification with increased accuracy of correct matches, especially for similarly shaped objects

Example: Can you tell in the left part of the point cloud whether it is an apple or an orange? This is only possible in RGB color. Conversely, a 2D camera would not be able to tell the difference between the photo of an apple and the real apple.

Color information

Color information helps improve scene details where depth information is lacking

Example: During depalletizing, two cartons are so close together on the pallet that they are recognized as one by the 3D camera. In the higher-resolution RGB data, however, a gap can be detected.

Reliable scene segmentation, if necessary enhanced by the use of deep learning (here: integration of prior scene knowledge), for example for the use of mobile robots

Example: Finding the floor in 3D is supported by color: asphalt gray probably belongs to road (floor).

Here, too, a combination can be helpful

Higher system reliability, for example in obstacle detection for automated guided vehicles

Reduced computational load: Find a container in 2D and analyze its fill level in this reduced ROI with 3D

Promotes scene understanding in humans, making it easier to set up and operate complex 3D systems

Ready for use: The ace 2 to blaze mounting bracket

A printable solution

If you want to mount an ace 2 or ace camera from Basler to the blaze-101 camera as shown in the picture, order the appropriate mounting bracket here.

Order mouting bracket here

An RGB-D application is exactly what you are looking for?

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