TY - GEN
T1 - Image based touristic monument classification using Graph Based Visual Saliency and Scale-Invariant Feature Transform
AU - Kalliatakis, Grigorios E.
AU - Kounalakis, Tsampikos
AU - Papadourakis, Georgios
AU - Triantafyllidis, Georgios A.
PY - 2012
Y1 - 2012
N2 - This paper presents an image-based application using Graph Based Visual Saliency (GB VS) and Scale-Invariant Feature Transform (SIFT), aiming at simple image classification of well-known touristic monuments in the geographic area of Heraklion, Crete, Greece. For this purpose, photographs taken at various sites of interest are being compared to an existing database containing photos of these sites at different angles and zoom. The time required in such application is an important element. To this goal, the proposed application employs SIFT algorithm to compare the user-taken photographs with the database photographs, that have been previously processed according to the Graph Based Visual Saliency technique, in order to minimize the "noise" of the monument's background and keep only the SIFT features that will help faster and more accurate classification. The application is then able to classify these photographs fast, helping the user to better understand what he sees and in which area he had this photograph.
AB - This paper presents an image-based application using Graph Based Visual Saliency (GB VS) and Scale-Invariant Feature Transform (SIFT), aiming at simple image classification of well-known touristic monuments in the geographic area of Heraklion, Crete, Greece. For this purpose, photographs taken at various sites of interest are being compared to an existing database containing photos of these sites at different angles and zoom. The time required in such application is an important element. To this goal, the proposed application employs SIFT algorithm to compare the user-taken photographs with the database photographs, that have been previously processed according to the Graph Based Visual Saliency technique, in order to minimize the "noise" of the monument's background and keep only the SIFT features that will help faster and more accurate classification. The application is then able to classify these photographs fast, helping the user to better understand what he sees and in which area he had this photograph.
KW - Graph Based Visual Saliency
KW - Image classification
KW - SIFT
UR - http://www.scopus.com/inward/record.url?scp=84864766809&partnerID=8YFLogxK
U2 - 10.2316/P.2012.779-027
DO - 10.2316/P.2012.779-027
M3 - Article in proceeding
AN - SCOPUS:84864766809
SN - 9780889869219
T3 - Proceedings of the IASTED International Conference on Computer Graphics and Imaging, CGIM 2012
SP - 261
EP - 266
BT - Proceedings of the IASTED International Conference on Computer Graphics and Imaging, CGIM 2012
T2 - IASTED International Conference on Computer Graphics and Imaging, CGIM 2012
Y2 - 18 June 2012 through 20 June 2012
ER -