A Method of Memory Reduction for Specific Object Recognition with a Bloomier Filter

LanguageEnglish
TypeProceedings of International Conferences
AuthorsKatsufumi Inoue, Koichi Kise
TitleA Method of Memory Reduction for Specific Object Recognition with a Bloomier Filter
JournalProceedings of the 2009 International Conference on Multimedia, Information Technology and its Applications (MITA2009)
Pagespp.27-28
ReviewedReviewed
DateAugust 2009
Research fieldsObject Recognition, Pattern recognition
KeyInoue2009_MITA (id=1102)

Abstract

Specific object recognition based on nearest neighbor search of feature vectors requires a huge amount of memory to store all feature vectors for distance calculation. To solve this problem, we propose a memory reduction method for specific object recognition with no distance calculation for matching feature vectors. The proposed method is characterized by the use of a Bloomier filter, which is far memory efficient than a hash table, 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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