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Comparison Between Multi-Vector Feature Space Method and Earth Mover's Distance Method In Similarity Searches of Images
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- Yamane Yasuo
- Language Processing Laboratory Fujitsu Laboratories Ltd.
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- Hoshiai Tadashi
- Language Processing Laboratory Fujitsu Laboratories Ltd.
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- Tsuda Hiroshi
- Language Processing Laboratory Fujitsu Laboratories Ltd.
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- Katayama Kaoru
- Graduate School of Engineering Tokyo Metropolitan University
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- Ohta Manabu
- Graduate School of Engineering Tokyo Metropolitan University
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- Ishikawa Hiroshi
- Graduate School of Engineering Tokyo Metropolitan University
Bibliographic Information
- Other Title
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- 画像の類似検索におけるマルチベクトル特徴空間方式とEarth Mover's Distance方式の比較(セッション4 : 情報検索)
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Description
There are some cases where dissimilar images are judged to be similar in using quadratic-form distance, a representative one in similarity searches of images. To address this problem, we proposed a multi-vector feature space method based on pseudo-Euclidean space and an oblique basis (MVPO). In this method, an image is represented by a solid consisting of multiple vectors; each vector corresponds to each feature. We also proposed D-distance as a distance between solids. A representative method similar to ours is Earth Mover's Distance (EMD), which is said to experimentally outperforms others including quadratic-form distance in precision. We show that EMD can be formalized as a distance in MVPO, and a reason why it outperforms quadratic-form distance. We also mention the difference between D-distance and EMD.
Journal
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- IPSJ SIG Notes
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IPSJ SIG Notes 2004 (45), 83-90, 2004-05-13
Information Processing Society of Japan (IPSJ)
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Details 詳細情報について
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- CRID
- 1573105977028623616
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- NII Article ID
- 110002911530
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- NII Book ID
- AN10114171
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- Text Lang
- ja
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- Data Source
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- CiNii Articles