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. In this paper 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.
|Original language||English (US)|
|Number of pages||8|
|Journal||Proceedings of the International Conference on Tools with Artificial Intelligence|
|State||Published - Dec 1 1998|
|Event||Proceedings of the 1998 IEEE 10th International Conference on Tools with Artificial Intelligence - Taipei, China|
Duration: Nov 10 1998 → Nov 12 1998
All Science Journal Classification (ASJC) codes