|Title:||3D sub-query expansion for improving sketch-based multi-view image retrieval||Authors:||Lin Y.-L.
|Issue Date:||2013||Start page/Pages:||3495-3502||Source:||IEEE International Conference on Computer Vision||Abstract:||
We propose a 3D sub-query expansion approach for boosting sketch-based multi-view image retrieval. The core idea of our method is to automatically convert two (guided) 2D sketches into an approximated 3D sketch model, and then generate multi-view sketches as expanded sub-queries to improve the retrieval performance. To learn the weights among synthesized views (sub-queries), we present a new multi-query feature to model the similarity between sub-queries and dataset images, and formulate it into a convex optimization problem. Our approach shows superior performance compared with the state-of-the-art approach on a public multi-view image dataset. Moreover, we also conduct sensitivity tests to analyze the parameters of our approach based on the gathered user sketches. ? 2013 IEEE.
|Appears in Collections:||資訊工程學系|
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