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A Bumblebee Stereo Camera mounted on a Pan-Tilt-Head aquires pairs of images, which are transformed to Point Clouds. Multiple Point Clouds are joined to a common Point Cloud.

In this video the internal data structure of the Point Clouds: the Octree is shown. With this tree structure many point cloud operations can be calculated much faster than with a simple list of points.

This video shows a simple scene with a box on a table and how it is seen by a stereo camera and a time-of-flight camera. All three camera views can be visualized at the same time in the same 3D-environment

In this video a marker detection of a known object (table plate) is shown. There is a discrepancy between the 3D-model of the table plate and the image plane at the far end of the table. In addition, the image and data inspection capabilities of ImageNet Designer are shown.

This video shows the integrated help in each ImageNets block which is displayed when the mouse cursor rests some time over the block. There is a general help for the whole block, a help for every input and output and for every property of a block. The author(s) can also be defined and displayed.

Feedbacks can be used to improve automatic detection even under changing illumination conditions. This is especially useful in service robotic applications.

This video shows a colored point cloud captured by a stereo camera. The point cloud is thresholded by a plane which is defined by a coordinate transformation frame. The frame itself is the output of a marker detection.

This video shows the calculation of a color point cloud and that the same functionality can be loaded in a SubNet Block.