DocumentCode :
2781864
Title :
Discovering the Local Co-occurring Patterns in Visual Categorization
Author :
Wang, Hongbin ; Miller, Paul ; Culverhouse, Phil F.
Author_Institution :
Queen´´s University Belfast, UK
fYear :
2006
fDate :
Nov. 2006
Firstpage :
6
Lastpage :
6
Abstract :
We present a novel visual representation, called local co-occurring patterns (LCPs), which consists of characteristic local features and the statistical co-occurance relations between them. The LCPs can be discovered using an associate rule mining algorithm. Experiments show that LCPs widely exist in a large image corpus, and are more discriminant than individual local features in visual categorization tasks such as subcategory and face recognition. Furthermore, state-of-the-art categorization performance was achieved on two test data-sets.
Keywords :
Airplanes; Face recognition; Feature extraction; Frequency; Image databases; Information technology; Motorcycles; Object recognition; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Video and Signal Based Surveillance, 2006. AVSS '06. IEEE International Conference on
Conference_Location :
Sydney, Australia
Print_ISBN :
0-7695-2688-8
Type :
conf
DOI :
10.1109/AVSS.2006.41
Filename :
4020665
Link To Document :
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