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Multimedia Systems

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04.05.2022 | Regular Paper

Feature representation for 3D object retrieval based on unconstrained multi-view

verfasst von: Bin Zhou, Xuanyin Wang

Erschienen in: Multimedia Systems | Ausgabe 5/2022

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Abstract

Reasonable and accurate image feature representation is the key to successful object retrieval. In this paper, we propose a 3D object feature representation method based on multiple views rather than a shape model. Unlike existing view-based methods that use pre-designed camera arrays to capture views, our method is flexible to implement by using several unconstrained views. Firstly, we generate a histogram of word frequencies to represent each view through local feature quantization. Then we integrate the histogram vectors of views belonging to the same object to generate a complete feature representation. Finally, similarity between two features is calculated for object retrieval. Several criteria are employed to evaluate the retrieval quality of the proposed method. Experimental results show that the integrated model feature is more effective and efficient than a set of individual image features and our approach is also competitive among several state-of-the-art methods.

Vorheriger Artikel Visual saliency detection via combining center prior and U-Net

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Titel: Feature representation for 3D object retrieval based on unconstrained multi-view
verfasst von: Bin Zhou
Xuanyin Wang
Publikationsdatum: 04.05.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Multimedia Systems / Ausgabe 5/2022
Print ISSN: 0942-4962
Elektronische ISSN: 1432-1882
DOI: https://doi.org/10.1007/s00530-022-00939-1

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