A New Multi-Level Attributed Graph Based Shape Matching Approach to Complex Template Design Feature Recognition Available to Purchase

Some 3D complex shapes such as stair and compound-hole in engineering design always contains various geometric face types, adjacent geometric constraints and typical design semantics. These 3D shapes can be defined as template design features because they are frequently reused for synchronous shape modeling to greatly accelerate design and analysis process. To recognize the complex template design features, we present a new multi-level attributed graph based shape matching approach. The core idea is the Multi-level Attributed Graph (MLAG), which describes not only the geometry face types such as plane and the geometry relationships between two adjacent faces such as tangency that are usually used for 3D shape retrieval and manufacturing feature recognition, but also the design semantic features among multiple adjacent faces even non-adjacent faces such as boss. Such design semantic feature will greatly benefit MLAG matching process, so that a complex template design feature can be efficiently recognized for design modification. Finally, two experiments with some kinds of template feature recognition are also shown to demonstrate the effectiveness of the proposed method.