3D Positioning with Just One Camera

Perspective Matching

MVTec uses perspective matching to determine the 3D position of an object from a planar subarea. The technology does not require a complete 3D shape model and only needs a single camera.

The software evaluates a planar area of the object within a defined ROI. From the projection of this area into the camera image, the software calculates the 3D position (location and orientation) of the object in space. The model is created by training with a pattern image of the object. This pattern represents the relevant planar part of the object used for matching.

Typical Applications

Perspective matching is used wherever the 3D position of an object must be accurately determined without creating a complete 3D model. This allows robotic gripping operations and measurement processes to be automated more robustly and efficiently.

 

3D alignment of components in assembly and inspection processes.

Pick-and-place applications in machine vision.

"Bin picking" with robots.

Applications in the automotive and robotics fields.

Measurement tasks on complex 3D objects after 3D alignment, such as position or distance checks.

 

Methods In MVTec Software

MVTec offers two complementary methods for perspective matching, tailored to object shape and appearance:

Deformable Matching (Perspective Deformable Matching)
Uses shape-based matching technologies. The software primarily focuses on object edges and can compensate for perspective distortions as well as slight deformations.

Descriptor-Based Matching
Works with "key points" (feature points) in the image. These points are described by their local surroundings and enable robust recognition even with changing viewpoints or lighting conditions.

In both cases, objects can be reliably localized with just a single camera, deriving their 3D position. This reduces hardware requirements, simplifies integration, and opens up flexible 3D vision solutions.

Only a planar part of the object is necessary to determine the 3D pose of the object by exploiting perspective matching techniques.
Only a planar part of the object is necessary to determine the 3D pose of the object by exploiting perspective matching techniques.
Calculating the 3D pose of objects by finding the trained deformable model.
Calculating the 3D pose of objects by finding the trained deformable model.

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