Fast similarity search in databases of 3D objects

• Published in: Proceedings Tenth IEEE International Conference on Tools with Artificial Intelligence (Cat. No.98CH36294) pp. 16 - 23
• Main Authors: Xiong Wang, Wang, J.T.L.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1998
• Subjects: Application software; Artificial intelligence; Biology computing; Computer vision; Image retrieval; Information retrieval; Information science; Joining processes; Search problems; Spatial databases
• ISBN: 0780352149; 9780780352148
• ISSN: 1082-3409; 2375-0197
• DOI: 10.1109/TAI.1998.744746

Given a database D of three dimensional (3D) objects and a target object Q, the similarity search problem (also known as good-match retrieval) is defined as finding the objects D in D that approximately match Q, possibly in the presence of rotation, translation, node insert, delete and relabeling in D or Q. This type of query arises in many AI applications. We study the similarity search problem and a class of related queries. We present a computer vision based technique called geometric hashing for processing these queries. Experimental results on a database of 3D molecules obtained from the National Cancer Institute indicate the good performance of the presented technique.