Summary: Scene classification is a useful, yet challenging problem
in computer vision. Two importat tasks for scene classification
are the image representation and the choice of the
classifier used for decision making. This paper proposes a
new technique for scene classification using combined classifiers
method. We run two classifiers based on different features:
GistCMCT and spatial MCT and combine the output
results to obtain the final class. In this way, we improve accuracy,
by taking advantage from the qualities of the two
descriptors, without increase the final size of the feature
vector. Experimental results on four used datasets demonstrate
that the proposed methods could achieve competitive
performance against previous methods.

Starting date: 07/08/2011
Deadline (months): 24

Participants:

Role	Name
Coordinator *	EVANDRO OTTONI TEATINI SALLES
Student Doctorate *	KARIN SATIE KOMATI
Student Doctorate *	KELLY ASSIS DE SOUZA GAZOLLI