Hierarchical component based object recognition

US7239929B2 · kind B2 · utility

Assignee

• MVTec Software GmbH · DE

Inventors

• Markus Ulrich · Hersbruck, DE
• Carsten Steger · Unterschleißheim, DE

Key dates

• Filing date: Aug 29, 2003
• Grant date: Jul 3, 2007
• Expiry date: Dec 12, 2024

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V10/772
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

The present invention provides a method for the recognition of objects in an image, where the objects may consist of an arbitrary number of parts that are allowed to move with respect to each other. In the offline phase the invention automatically learns the relative movements of the single object parts from a sequence of example images and builds a hierarchical model that incorporates a description of the single object parts, the relations between the parts, and an efficient search strategy. This is done by analyzing the pose variations (e.g., variations in position, orientation, and scale) of the single object parts in the example images. The poses can be obtained by an arbitrary similarity measure for object recognition, e.g., normalized cross correlation, Hausdorff distance, generalized Hough transform, the modification of the generalized Hough transform, or the similarity measure. In the online phase the invention uses the hierarchical model to efficiently find the entire object in the search image. During the online phase only valid instances of the object are found, i.e., the object parts are not searched for in the entire image but only in a restricted portion of parameter …