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Detail of Publication

Text Language Japanese
Authors Katsufumi Inoue, Koichi Kise
Title Memory Reduction with Bloomier Filters for Specific Object Recognition
Journal IEICE Technical Report
Presentation number PRMU2009-56
Pages pp.101-106
Reviewed or not Not reviewed
Month & Year June 2009
Abstract Specific object recognition based on nearest neighbor search of feature vectors required a huge amount of memory to store all feature vectors for distance calculation. Tosolve this problem, we propose a memory reduction method for specific object recognition with a strategy of skipping the distance calculation of feature vectors. The proposed method is characterized by the use of Bloomier filters, which are far memory efficient than hash tables, for the storage of feature vectors. The proposed method is evaluated based on experiments of planar and 3D specific object recognition in comparison to a method with a hash table.
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