Learning Object Groups for Scene Recognition

Hao Su; Shan Liao

doi:10.4028/www.scientific.net/AMR.998-999.1028

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 998-999Learning Object Groups for Scene Recognition

Learning Object Groups for Scene Recognition

Abstract:

Scene recognition is an important task for many computer vision and robotics applications. Recent progress in high-level object-based image representation has shown superior performance on scene classification tasks. In this work, we make an observation that groups of objects tend to co-occur frequently in a scene. We therefore propose to a novel framework that automatically learns object groups, and use them to build an image representation for scene recognition tasks. We model each object group as a template that explicitly encodes the spatial configurations of objects. To encourage the informativeness and discriminability, we learn the object group templates in a sparse filtering framework. Experiment results show that our object group representation could achieve state-of-the-art performance for both scene discovery and scene classification tasks.

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Periodical:

Advanced Materials Research (Volumes 998-999)

Pages:

1028-1032

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.998-999.1028

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Online since:

July 2014

Authors:

Hao Su*, Shan Liao

Keywords:

Scene Recognition, Sparse Filtering

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* - Corresponding Author

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