DocumentCode
3270584
Title
Subregion based local descriptor
Author
Xiaojie Dong ; Erqi Liu ; Jie Yang
Author_Institution
Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China
fYear
2013
fDate
15-18 Sept. 2013
Firstpage
250
Lastpage
254
Abstract
A novel distinctive descriptor named MSOGH is proposed, which is able to well represent the interest region and is robust to photometric transformations and geometric transformations. According to intensity order, subregions are firstly constructed. Then feature descriptor of the subregion is computed by point permutation of the sample points in each subregion. Finally, feature descriptor of the region is formed by concatenating all subregion feature descriptors. The discriminative power of the proposed descriptor is compared with 5 major existing region descriptors (MROGH, SIFT, GLOH, PCA-SIFT and spin images). Extensive experimental results show that the proposed descriptor achieves better performance than state-of-the-art descriptors.
Keywords
feature extraction; image representation; GLOH; MROGH; MSOGH; PCA-SIFT; geometric transformations; intensity order; interest region representation; photometric transformations; point permutation; spin images; subregion based local descriptor; subregion feature descriptor; Color; Detectors; Feature extraction; Histograms; Robustness; Standards; Vectors; Image Matching; Local Descriptor; Performance Evaluation; Subregion;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location
Melbourne, VIC
Type
conf
DOI
10.1109/ICIP.2013.6738052
Filename
6738052
Link To Document