Japanese / English

Detail of Publication

Text Language Japanese
Authors Katsufumi Inoue,Koichi Kise
Title Compressed Representation of Feature Vectors Using a Bloomier Filter and Its Application to Specific Object Recognition
Journal Proceedings of MIRU 2009
Presentation number OS12-2
Pages pp.343-350
Reviewed or not Not reviewed
Month & Year July 2009
Abstract Nearest neighbor search of feature vectors representing local features is often employed for specific object recognition. In such a method, it is required to store all feature vectors for distance calculation. The number of feature vectors is , in general, so large that a huge amount of memory is needed for their storage. A way to solve this problem is to skip the distance calculation for recognition. In this paper, we propose a method of object recognition without distance calculation. The characteristic point of the proposed method is to use a Bloomier filter, which is far memory efficinet than hash tables, for the storage of feature vectors. From experiments of planar and 3D specific object recognition, the proposed method is evaluated in comparison to a method with a hash table.
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