Aspect-Trees: Generation and Interpretation

摘要

This contribution presents a new approach to the recognition of a priori known 3-D objects in single 2-D images. The underlying model is embedded in the domain of CAD-based vision using a viewer-centered approach to generate a set of normalized views. They serve as a basis for an optimal selection of properties of features. The aspect idea is used for grouping the values of the properties into aspect-trees. The aim of this approach is to identify the correct view of an object seen in the image and thereby to distinguish between different objects. This is achieved with an appropriate traversion of the aspect-trees which proves the ability of the image interpretation system Aspik to recognize complex objects in different environments robustly and efficiently. The time complexity for recognizing nonoccluded objects is O (n2 · m), where n is the number of the considered aspect-trees of the object and m the number of image features.