The semantic interpretation of natural scenes, generally so obvious and effortless for humans, still remains a challenge in computer vision. We intend to design classifiers able to annotate images with keywords. Firstly, we propose an image representation appropriate for scene description: images are segmented into regions and indexed according to the presence of given region types. Secondly, we propound a classification scheme de- signed to separate images in the descriptor space. This is achieved by combining feature selection and kernel-method-based classification.

Image classifiers for scene analysis

Amato G
2004

Abstract

The semantic interpretation of natural scenes, generally so obvious and effortless for humans, still remains a challenge in computer vision. We intend to design classifiers able to annotate images with keywords. Firstly, we propose an image representation appropriate for scene description: images are segmented into regions and indexed according to the presence of given region types. Secondly, we propound a classification scheme de- signed to separate images in the descriptor space. This is achieved by combining feature selection and kernel-method-based classification.
2004
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
9781402041785
Scene analysis
Feature selection
Image classification
Kernel methods
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/371110
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