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Complex spatial region representation and similar matching for multi-object image retrieval
Author(s): Dong Liu; Shengsheng Wang; Weiqing Li; Shanglin Li; Yaohui Liu; Fang Fang
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Paper Abstract

Spatial relationship and structure models play an important role in various computer vision tasks. Many spatial models focus on global relationship modeling and ignore the detail of the internal structure. This will cause a poor performance in capturing discriminative features for a complex multi-object image. In this paper, we present a novel spatial structure model for complex regions with explicit similar measure. Three aspects of our method should be noted in comparison to the previous approaches. First, we propose a detailed layered graph model for representing complex regions, which has complete description performance and even the slight differences among the local objects can be also recognized. We further provide similar matching algorithms for topological structures based on the detailed layered graph model. Finally, an effective retrieval framework is proposed and applied to multi-object image retrieval. Rigorous experimental evaluations on two datasets demonstrate that the proposed method outperforms other prevailing approaches.

Paper Details

Date Published: 3 January 2020
PDF: 8 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113731H (3 January 2020); doi: 10.1117/12.2557613
Show Author Affiliations
Dong Liu, Xiangnan Univ. (China)
Shengsheng Wang, Jilin Univ. (China)
Weiqing Li, Xiangnan Univ. (China)
Shanglin Li, Xiangnan Univ. (China)
Yaohui Liu, Xiangnan Univ. (China)
Fang Fang, Xiangnan Univ. (China)

Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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