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International Journal of Multimedia Information Retrieval
Erschienen in: International Journal of Multimedia Information Retrieval 4/2022

26.08.2022 | Regular Paper

Similar interior coordination image retrieval with multi-view features

verfasst von: Ren Togo, Yuki Honma, Maiku Abe, Takahiro Ogawa, Miki Haseyama

Erschienen in: International Journal of Multimedia Information Retrieval | Ausgabe 4/2022

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Abstract

This paper presents a novel similar image retrieval method for interior coordination. Interior coordination is very familiar; however, it is still an abstract and difficult concept. Even if we are involved in coordination every day, it does not mean we can become professional coordinators. By realizing the retrieval that can provide similar interior coordination images from a query room image, inspiring users’ ideas for interior coordination becomes feasible. In the proposed method, we extract image features specialized for interior coordination and realize similar interior coordination image retrieval. We employ multi-view features: object-based, color-based, and semantic-based features, in the feature extraction phase. The extracted features are used to calculate similarity between the query image and the database images for the retrieval. We conducted experiments using a sophisticated real-world interior coordination image dataset. Furthermore, we qualitatively and quantitatively evaluated the effectiveness of the proposed method.
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Metadaten
Titel
Similar interior coordination image retrieval with multi-view features
verfasst von
Ren Togo
Yuki Honma
Maiku Abe
Takahiro Ogawa
Miki Haseyama
Publikationsdatum
26.08.2022
Verlag
Springer London
Erschienen in
International Journal of Multimedia Information Retrieval / Ausgabe 4/2022
Print ISSN: 2192-6611
Elektronische ISSN: 2192-662X
DOI
https://doi.org/10.1007/s13735-022-00247-4

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