Designers spend a significant amount of time searching for information that is available but cannot be located through traditional methods. Rectification of errors that have been committed due to lack of information is a costly way to learn. Nevertheless this has become a de facto process for new product design. A significant amount of information generated during the lifecycle of a product is associated with 3D models. Reuse of this information can significantly shorten lead times and reduce costs during a product's lifecycle. This project deals with an innovative approach to search for 3D models. 3D search offers an alternative means to retrieve design knowledge that is intimately associated with 3D geometry. 3D models are represented by a hierarchical skeletal graph representation rich with local information. The skeletal graph representation preserves geometry and topology of the model with good fidelity. Critical issues such as algorithms for converting a model into a skeletal graph, search system efficiency, semantic gap reduction and the subjectivity of the similarity definition are addressed.

Primary Faculty:
Subramani Sellamani , Ramanathan Muthuganapathy , and Karthik Ramani
Associated Faculty:
Christoph Hoffman

Suyu Hou , Yagnanarayanan Kalyanaraman , Amit Jain , Justin Stamen , Sundar Mururgappan , and Min Liu

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