Scene Identification using Discriminative Patterns

Abstract : With the proliferation of camera phones, new information retrieval applications will emerge. The image of a scene captured by a camera phone can be a query to a remote server to identify the scene and return relevant information. But unconstrained scene identification is an open problem. In this paper, we propose a discriminative measure to rank image patterns sampled from target scene classes. Support vector classifiers are then trained using top discriminative patterns for scene identification using voting. We demonstrate our generic approach on two scene databases (ZuBuD and STOIC) with promising results.
Type de document :
Communication dans un congrès
The 18th International Conference on Pattern Recognition ICPR2006, 2006, Unknown, Hong Kong SAR China. pp.642--645, 2006
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https://hal.inria.fr/hal-00953898
Contributeur : Marie-Christine Fauvet <>
Soumis le : vendredi 28 février 2014 - 16:03:42
Dernière modification le : mardi 24 avril 2018 - 13:29:34

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  • HAL Id : hal-00953898, version 1

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Joo-Hwee Lim, Jean-Pierre Chevallet, Sheng Gao. Scene Identification using Discriminative Patterns. The 18th International Conference on Pattern Recognition ICPR2006, 2006, Unknown, Hong Kong SAR China. pp.642--645, 2006. 〈hal-00953898〉

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