Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 14, Issue 6, Pages 851-855Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2017.2683495
Keywords
Feature extraction; Fisher vector; object detection; ring pyramid pooling (RPP); rotation-invariant matrix (RIM)
Categories
Funding
- National Natural Science Foundation of China [61403375, 61472119, 91338202]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology
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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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