Memory Reduction Method for Specific Object Recognition with the BloomierFilter and Its Experimental Evaluation

LanguageJapanese
TypeJournal Articles
AuthorsKatsufumi Inoue, Koichi Kise
TitleMemory Reduction Method for Specific Object Recognition with the BloomierFilter and Its Experimental Evaluation
JournalTrans. IEICE
Vol.J93-D
No.8
Pagespp.1407-1416
ReviewedReviewed
DateAugust 2010
Research fieldsObject Recognition
KeyInoue2010_IEICE (id=1155)

Abstract

Reduction of the amount of memory is an important issue for specific object recognition. The bag-of-features representation (BOF) based on vector quantization of feature vectors is known to be effective for the reduction. However, BOF also reduces the discriminative power of feature vectors, which results in lowering the recognition accuracy. To solve this problem, we propose a new memory reduction method using the Bloomier filter which is a probabilistic and compact data structure for storing a large amount of feature vectors. Experimental results show that the proposed method achieves 1/2 or more reduction as compared with conventional methods.

Note

PDF file is available at IEICE Transactions online (in Japanese).

Export this publication

Format definition
Edits apply immediately and stay in effect until you pick a style again or reset. First line is the default; add lines like "book: …" to override per type.
How to write the definition

Insert a field with braces like {authors}. A part enclosed in [ ... ] is omitted entirely when any field inside it is empty. Available fields:

{authors}{authors_and}{authors_ja}{authors_ja_tight}{authors_en}{authors_en_and}{authors_tight}{first_author}{title}{title_ja}{title_en}{journal}{journal_ja}{journal_en}{book_title}{volume}{number}{series}{presen_id}{pages}{pp}{num_pages}{year}{month}{month_en}{month_short}{ym}{date}{date_ja}{date_en}{publisher}{address}{location}{review}{review_ja}{review_en}{reviewed_mark}{presen_type}{type}{type_label}{doi}{url}{key}{awards}

← Back to list