Title: Feature Extraction by Rotation-Invariant Matrix Representation for Object Detection in Aerial Image
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| Authors: Wang, GL; Wang, XC; Fan, B; Pan, CH
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| Author Full Names: Wang, Guoli; Wang, Xinchao; Fan, Bin; Pan, Chunhong
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| Source: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 14 (6):851-855; 10.1109/LGRS.2017.2683495 JUN 2017
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| Language: English
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| Abstract: This letter proposes a novel rotation-invariant feature for object detection in optical remote sensing images. Different from previous rotation-invariant features, the proposed rotation-invariant matrix (RIM) can incorporate partial angular spatial information in addition to radial spatial information. Moreover, it can be further calculated between different rings for a redundant representation of the spatial layout. Based on the RIM, we further propose an RIM_ FV_ RPP feature for object detection. For an image region, we first densely extract RIM features from overlapping blocks; then, these RIM features are encoded into Fisher vectors; finally, a pyramid pooling strategy that hierarchically accumulates Fisher vectors in ring subregions is used to encode richer spatial information while maintaining rotation invariance. Both of the RIM and RIM_ FV_ RPP are rotation invariant. Experiments on airplane and car detection in optical remote sensing images demonstrate the superiority of our feature to the state of the art.
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| ISSN: 1545-598X
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| eISSN: 1558-0571
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| IDS Number: EV9FX
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| Unique ID: WOS:000402092300013
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