Advertisement
Published in:
2006 | OriginalPaper | Chapter
A Probability-Based Unified 3D Shape Search
Authors : Suyu Hou, Karthik Ramani
Published in: Semantic Multimedia
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
We present a probability-based unified search framework composed of semi-supervised semantic clustering and then a constraint-based shape matching. Given a query, we propose to use an ensemble of classifiers to estimate the likelihood of the query belonging to each category by exploring the strengths from individual classifiers. Three descriptors driven by Multilevel-Detail shape descriptions have been used to generate the classifier independently. A weighted linear combination rule, called MCE (Minimum Classification Error), is adapted to support high-quality downstream application of the unified search. Experiments are conducted to evaluate the proposed framework using the Engineering Shape Benchmark database. The results have shown that search effectiveness is significantly improved by enforcing the probability-based semantic constraints to shape-based similarity retrieval.