Abswacf-Similarity search in 3D ohject datahases is hecoming a n important pmhlem 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 impurily measure, widely used in the context of decision trees. We propose a method for the a priori estimation of individual feature vector perfurmance 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.
The authors of REF introduce two methods for improving the effectiveness in a retrieval system that operates on multiple representations of 3D objects.
Using entropy impurity for improved 3D object similarity search
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)
2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)
Computer Science