Using entropy impurity for improved 3D object similarity search
Benjamín Bustos, Daniel A. Keim, Dietmar Saupe, Tobias Schreck, Dejan V. Vranić · 2005
Similarity search in 3D object databases is becoming an important problem in multimedia retrieval, with many practical applications. We investigate methods for improving the effectiveness in a retrieval system that implements multiple feature extraction algorithms to choose from. Our techniques are based on the entropy impurity measure, widely used in the context of decision trees. We propose a method for the a priori estimation of individual feature vector performance, given a query. We then define two approaches that use this estimator to improve the retrieval effectiveness. Our experimental results show that significant improvements are achievable using these methods.