DocumentCode
589367
Title
Combining Holistic and Object-Based Approaches for Scene Classification
Author
Zenghai Chen ; Zheru Chi ; Hong Fu ; Dagan Feng
Author_Institution
Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Volume
1
fYear
2012
fDate
28-29 Oct. 2012
Firstpage
65
Lastpage
68
Abstract
There are two main approaches for scene classification: holistic and object-based. Holistic approach is good at representing scenes with simple content. However, since it does not take into account the internal object relationship, holistic approach does not well characterize complex scenes with multiple objects. by contrast, object-based approach estimates the scene class by analyzing the object co-occurrence information, as a result of which it is advantageous in characterizing scenes with complex content. but object-based approach is not good at classifying simple scenes. in this paper, we combine holistic and object-based approaches for scene classification. the proposed combinatory approach is able to take advantages of the two approaches. Several state-of-the-art holistic and object-based approaches are compared. the experiments conducted on a widely-used scene dataset demonstrate the superiors performance of the combinatory approach.
Keywords
combinatorial mathematics; image classification; natural scenes; combinatory approach; complex scenes; holistic approaches; internal object relationship; object cooccurrence information; object-based approaches; scene classification; scene dataset; Accuracy; Computed tomography; Computer vision; Lakes; Rivers; Semantics; Visualization; CENTRIST; holistic approach; object-based approach; scene classification; spatial pyramid matching (SPM);
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4673-2646-9
Type
conf
DOI
10.1109/ISCID.2012.25
Filename
6406876
Link To Document