DocumentCode :
3455704
Title :
Multi-Scale Gist Feature Representation for Building Recognition
Author :
Cai-rong Zhao ; Chuan-cai Liu
Author_Institution :
Dept. of Phys. & Electron., Minjian Coll., Fuzhou, China
fYear :
2010
fDate :
21-23 Oct. 2010
Firstpage :
1
Lastpage :
5
Abstract :
Building recognition is a relatively specific recognition task in object recognition, which is a challenging task since it encounters rotation, illumination changes, occlusion, etc. But human can recognize the gist of a novel image in a single glance despite of its complexity. Inspired by this human vision characteristic, we describe a new building recognition model, called multi-scale gist feature representation model,which captures a holistic and low-dimensional representation of the structure of a building image. To evaluate the performance of our proposed model, experiments were carried out on the Sheffield buildings database, compared with the existing works:(a) the visual gist based building recognition model (VGBR); (b) the hierarchical building recognition model (HBR). The results show that the proposed model is effective and robust.
Keywords :
image recognition; image representation; structural engineering computing; Sheffield buildings database; building recognition; multiscale gist feature representation; object recognition; Buildings; Data models; Feature extraction; Image color analysis; Image recognition; Object recognition; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (CCPR), 2010 Chinese Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-7209-3
Electronic_ISBN :
978-1-4244-7210-9
Type :
conf
DOI :
10.1109/CCPR.2010.5659131
Filename :
5659131
Link To Document :
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