| 摘要 |
A coherent phrase model for near-duplicate image retrieval enforces coherency across multiple descriptors for every local region. Two types of visual phrase (FCP and SCP) are employed to represent feature and spatial coherency and can be utilized without increasing the computational complexity. The FCP utilizes the information of different features by enforcing the feature coherency across multiple types of descriptors for every local region, and the SCP utilizes spatial information by enforcing the spatial coherency across the spatial neighborhoods of different sizes around every local region. Moreover, the disclosed model improves the matching accuracy by reducing the number of false matches and preserves the matching efficiency because of the sparsity of the representation.
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