Fauqueur, J and Kingsbury, N and Anderson, R (2005) Semantic Discriminant mapping for classification and browsing of remote sensing textures and objects. Proceedings - International Conference on Image Processing, ICIP, 2. pp. 846-849. ISSN 1522-4880Full text not available from this repository.
We present a new approach based on Discriminant Analysis to map a high dimensional image feature space onto a subspace which has the following advantages: 1. each dimension corresponds to a semantic likelihood, 2. an efficient and simple multiclass classifier is proposed and 3. it is low dimensional. This mapping is learnt from a given set of labeled images with a class groundtruth. In the new space a classifier is naturally derived which performs as well as a linear SVM. We will show that projecting images in this new space provides a database browsing tool which is meaningful to the user. Results are presented on a remote sensing database with eight classes, made available online. The output semantic space is a low dimensional feature space which opens perspectives for other recognition tasks. © 2005 IEEE.
|Divisions:||Div F > Signal Processing and Communications|
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|Date Deposited:||09 Dec 2016 17:54|
|Last Modified:||24 Feb 2017 23:05|