CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Exploring Local and Overall Ordinal Information for Robust Feature Description
Zhenhua Wang1; Bin Fan1; Gang Wang2; Fuchao Wu1
Source PublicationIEEE Transactions on Pattern Analysis and Machine Intelligence
2016
Volume38Issue:11Pages:2198-2211
AbstractThis paper aims to build robust feature descriptors by exploring intensity order information in a patch. To this end, the local intensity order pattern (LIOP) and the overall intensity order pattern (OIOP) are proposed to effectively encode intensity order information of each pixel in different aspects. Specifically, LIOP captures the local ordinal information by using the intensity relationships among all the neighbouring sampling points around a pixel, while OIOP exploits the coarsely quantized overall intensity order of these sampling points. These two kinds of patterns are then separately aggregated into different ordinal bins, leading to two kinds of feature descriptors. Furthermore, as these two kinds of descriptors could encode complementary ordinal information, they are combined together to obtain a discriminative and compact mixed intensity order pattern descriptor. All these descriptors are constructed on the basis of relative relationships of intensities in a rotationally invariant way, making them be inherently invariant to image rotation and any monotonic intensity changes. Experimental results on image matching and object recognition are encouraging, demonstrating the superiorities of our descriptors over the state of the art.
KeywordFeature Description Intensity Order Illumination Invariance Image Matching
Indexed BySCI
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19696
Collection模式识别国家重点实验室_先进数据分析与学习
Corresponding AuthorBin Fan
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.National University of Singapore
Recommended Citation
GB/T 7714
Zhenhua Wang,Bin Fan,Gang Wang,et al. Exploring Local and Overall Ordinal Information for Robust Feature Description[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,38(11):2198-2211.
APA Zhenhua Wang,Bin Fan,Gang Wang,&Fuchao Wu.(2016).Exploring Local and Overall Ordinal Information for Robust Feature Description.IEEE Transactions on Pattern Analysis and Machine Intelligence,38(11),2198-2211.
MLA Zhenhua Wang,et al."Exploring Local and Overall Ordinal Information for Robust Feature Description".IEEE Transactions on Pattern Analysis and Machine Intelligence 38.11(2016):2198-2211.
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