Improved scene classification using efficient low-level features and semantic cues

Show full item record

Title: Improved scene classification using efficient low-level features and semantic cues
Author: Serrano, Navid; Savakis, Andreas; Lou, Jiebo
Abstract: Prior research in scene classification has focused on mapping a set of classic low-level vision features to semantically meaningful categories using a classifier engine. In this paper, we propose improving the established paradigm by using a simplified low-level feature set to predict multiple semantic scene attributes that are integrated probabilistically to obtain a final indoor/outdoor scene classification. An initial indoor/outdoor prediction is obtained by classifying computationally efficient, low-dimensional color and wavelet texture features using support vector machines. Similar low-level features can also be used to explicitly predict the presence of semantic features including grass and sky. The semantic scene attributes are then integrated using a Bayesian network designed for improved indoor/outdoor scene classification.
Record URI: http://hdl.handle.net/1850/10744
Date: 2004

Files in this item

Files Size Format View
ASavakisArticle2004.pdf 773.6Kb PDF View/Open

The following license files are associated with this item:

This item appears in the following Collection(s)

Show full item record

Search RIT DML


Advanced Search

Browse