Laplace gradient based Discriminative and Contrast Invertible descriptor
The performance of local descriptors such as SIFT drops under severe illumination changes. In this paper, we propose a Discriminative and Contrast Invertible (DCI) local feature descriptor. In order to increase the discriminative ability of the descriptor under illumination changes, a Laplace gradie...
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Published in | 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 1842 - 1846 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.03.2017
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Subjects | |
Online Access | Get full text |
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Summary: | The performance of local descriptors such as SIFT drops under severe illumination changes. In this paper, we propose a Discriminative and Contrast Invertible (DCI) local feature descriptor. In order to increase the discriminative ability of the descriptor under illumination changes, a Laplace gradient based histogram is proposed. Moreover, a robust contrast flipping estimate is proposed based on the divergence of a local region. Experiments on fine-grained object recognition and retrieval applications demonstrate the superior performance of the DCI descriptor to others. |
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ISSN: | 2379-190X |
DOI: | 10.1109/ICASSP.2017.7952475 |