Japanese / English

Detail of Publication

Text Language Japanese
Authors Katsufumi Inoue, Koichi Kise
Title Memory Reduction Method for Specific Object Recognition with the BloomierFilter and Its Experimental Evaluation
Journal Trans. IEICE
Vol. J93-D
No. 8
Pages pp.1407-1416
Reviewed or not Reviewed
Month & Year August 2010
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.
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