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Object discovery in high-resolution remote sensing images: a semantic perspective

Authors:

Vijayalakshmi Atluri,

Nabil R. AdamAuthors Info & Claims

Knowledge and Information Systems, Volume 19, Issue 2

Pages 211 - 233

Published: 01 May 2009 Publication History

Abstract

Given its importance, the problem of object discovery in high-resolution remote-sensing (HRRS) imagery has received a lot of attention in the literature. Despite the vast amount of expert endeavor spent on this problem, more efforts have been expected to discover and utilize hidden semantics of images for object detection. To that end, in this paper, we address this problem from two semantic perspectives. First, we propose a semantic-aware two-stage image segmentation approach, which preserves the semantics of real-world objects during the segmentation process. Second, to better capture semantic features for object discovery, we exploit a hyperclique pattern discovery method to find complex objects that consist of several co-existing individual objects that usually form a unique semantic concept. We consider the identified groups of co-existing objects as new feature sets and feed them into the learning model for better performance of image retrieval. Experiments with real-world datasets show that, with reliable segmentation and new semantic features as starting points, we can improve the performance of object discovery in terms of various external criteria.

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Cited By

Vanegas MBloch IInglada J(2019)Fuzzy constraint satisfaction problem for model-based image interpretationFuzzy Sets and Systems10.1016/j.fss.2014.10.025286:C(1-29)Online publication date: 3-Jan-2019
https://dl.acm.org/doi/10.1016/j.fss.2014.10.025
Thi Ngoc Chau VChittayasothorn S(2018)A conceptual schema-based temporal meta database schemas generation technique for 3D objectsKnowledge and Information Systems10.5555/3225651.322589724:1(113-147)Online publication date: 29-Dec-2018
https://dl.acm.org/doi/10.5555/3225651.3225897
Shi MSun XTao DXu CBaciu GLiu H(2015)Exploring Spatial Correlation for Visual Object RetrievalACM Transactions on Intelligent Systems and Technology10.1145/26415766:2(1-21)Online publication date: 31-Mar-2015
https://dl.acm.org/doi/10.1145/2641576

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cover image Knowledge and Information Systems

Knowledge and Information Systems Volume 19, Issue 2

May 2009

132 pages

ISSN:0219-1377

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Copyright © Copyright © 2009 Springer-Verlag London Limited.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 May 2009

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Cited By

Vanegas MBloch IInglada J(2019)Fuzzy constraint satisfaction problem for model-based image interpretationFuzzy Sets and Systems10.1016/j.fss.2014.10.025286:C(1-29)Online publication date: 3-Jan-2019
https://dl.acm.org/doi/10.1016/j.fss.2014.10.025
Thi Ngoc Chau VChittayasothorn S(2018)A conceptual schema-based temporal meta database schemas generation technique for 3D objectsKnowledge and Information Systems10.5555/3225651.322589724:1(113-147)Online publication date: 29-Dec-2018
https://dl.acm.org/doi/10.5555/3225651.3225897
Shi MSun XTao DXu CBaciu GLiu H(2015)Exploring Spatial Correlation for Visual Object RetrievalACM Transactions on Intelligent Systems and Technology10.1145/26415766:2(1-21)Online publication date: 31-Mar-2015
https://dl.acm.org/doi/10.1145/2641576

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