scholarly journals Multilinear Supervised Neighborhood Preserving Embedding Analysis of Local Descriptor Tensor

10.5772/37457 ◽  
2012 ◽  
Author(s):  
Xian-Hua Han ◽  
Yen-Wei Che
Keyword(s):  
Local Descriptor

Local Descriptor-based Multi-Prototype Network for Few-shot Learning

2021 ◽  
pp. 107935
Author(s):  
Hongwei Huang ◽  
Zhangkai Wu ◽  
Wenbin Li ◽  
Jing Huo ◽  
Yang Gao
Keyword(s):  
Local Descriptor

scholarly journals CGCI-SIFT: A More Efficient and Compact Representation of Local Descriptor

2013 ◽  
Vol 13 (3) ◽  
pp. 132-141 ◽  
Author(s):  
Dongliang Su ◽  
Jian Wu ◽  
Zhiming Cui ◽  
Victor S. Sheng ◽  
Shengrong Gong
Keyword(s):  
Peripheral Region ◽  
Intensity Difference ◽  
Compact Representation ◽  
Interest Point ◽  
Local Descriptor ◽  
Geometric Transformations ◽  
Intensity Information ◽  
Matching Efficiency ◽  
Inner Region ◽  
Better Than

This paper proposes a novel invariant local descriptor, a combination of gradient histograms with contrast intensity (CGCI), for image matching and object recognition. Considering the different contributions of sub-regions inside a local interest region to an interest point, we divide the local interest region around the interest point into two main sub-regions: an inner region and a peripheral region. Then we describe the divided regions with gradient histogram information for the inner region and contrast intensity information for the peripheral region respectively. The contrast intensity information is defined as intensity difference between an interest point and other pixels in the local region. Our experimental results demonstrate that the proposed descriptor performs better than SIFT and its variants PCA-SIFT and SURF with various optical and geometric transformations. It also has better matching efficiency than SIFT and its variants PCA-SIFT and SURF, and has the potential to be used in a variety of realtime applications.

scholarly journals Supervised Local Descriptor Learning for Human Action Recognition

2017 ◽  
Vol 19 (9) ◽  
pp. 2056-2065 ◽  
Author(s):  
Xiantong Zhen ◽  
Feng Zheng ◽  
Ling Shao ◽  
Xianbin Cao ◽  
Dan Xu
Keyword(s):  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action ◽  
Local Descriptor
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