DocumentCode :
595318
Title :
Object clique representation for scene classification
Author :
Jingjing Chen ; Xiaochun Cao ; Bao Zhang
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2829
Lastpage :
2832
Abstract :
High-level visual recognition such as scene classification is a challenging task in computer vision. In this paper, we propose an image descriptor based on semantic cliques obtained by high-order pure dependence, and the image is represented by a vector whose element denotes the probability of containing each object cliques. Compared with using single objects as attributes, such representation carries corresponding semantic information, making it more suitable for highlevel visual recognition tasks. The experiments show that our object cliques as attributes for scene representation improves the accuracy of image classification.
Keywords :
computer vision; image classification; image representation; natural scenes; object recognition; probability; semantic Web; computer vision; image classification; image descriptor; image representation; object clique representation; probability; scene classification; scene representation; semantic cliques; semantic information; visual recognition; Accuracy; Airports; Detectors; Image recognition; Semantics; Support vector machines; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460754
Link To Document :
بازگشت