Moose vs. Mole: A Comparative Study

Moose vs. Mole: A Comparative Study

In the world of 3D scanning, precision and accuracy are paramount. We’ve put our latest scanner, Moose, to the test against Mole, using common scanning objects for comparison. Each object was scanned only once, without any editing, and the same point cloud fusion parameters were used across the board.

Athletic Shoes: A Test of Resolution

Shoes are common scanning objects, but complex fabrics and dark-colored shoes challenge the point cloud algorithm and scanner resolution.

 

-The red parts are black areas. Mole struggles to scan these areas and often produces noise after scanning. Moose, on the other hand, can accurately scan the black parts, resulting in a very clean point cloud.

 
-When facing complex mesh surfaces, Moose demonstrates the advantage of AI processing. Each grid on the shoe mesh is arranged very regularly, clean and exquisite.

 

Metal Parts: A Test of Accuracy and Scanning Range

Parts are precision scanning objects that test the scanner’s accuracy and scanning range.

 
-Moose’s accuracy error is ≤0.01mm, while Mole’s is ≈0.02mm.
 
-Moose’s 100mm scan depth can scan deeper into the object, making it easier to scan the complete structure of the object.

 

Human Hand: A Test of Tracking Ability and Point Cloud Fusion Algorithm

The human hand is a complex-angle scanning object that tests the scanner’s tracking ability and point cloud fusion algorithm.
 
-Thanks to the blue light system, Moose is less affected by shallow transparent objects and can correctly form the point cloud of the fingernails.
-Moose’s 0.07mm resolution can make the wrinkles at the finger joints clearly visible.
 
-When facing complex-angle objects, Moose’s AI Tracking plays a key role again, ensuring that complex camera movement paths do not lose tracking and can scan multiple angles in one go without pausing.
In conclusion, whether it’s resolution, accuracy, or tracking ability, Moose stands out as a superior 3D scanning solution.

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