Memory Reduction with Bloomier Filters for Specific Object Recognition
Language
Japanese
Type
Proceedings of Japanese Conferences
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
Not reviewed
Date
June 2009
Research fields
Object Recognition, Pattern recognition
Key
Inoue2009_IEICEPRMU_Memory (id=1091)
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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