An efficient radix trie-based semantic visual indexing model for large-scale image retrieval in cloud environment

2020 ◽  
Author(s):  
N. Krishnaraj ◽  
Mohamed Elhoseny ◽  
E. Laxmi Lydia ◽  
K. Shankar ◽  
Omar ALDabbas
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Cloud Environment ◽  
Indexing Model ◽  
Large Scale Image Retrieval

Ratio Voting: A New Voting Strategy for Large-Scale Image Retrieval

2012 ◽  
Author(s):  
Yusuke Uchida ◽  
Koichi Takagi ◽  
Shigeyuki Sakazawa
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Large Scale Image Retrieval ◽  
Voting Strategy

An Enhanced Deep Hashing Method for Large-Scale Image Retrieval

2019 ◽  
pp. 382-393
Author(s):  
Cong Chen ◽  
Weiqin Tong ◽  
Xuehai Ding ◽  
Xiaoli Zhi
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Deep Hashing ◽  
Large Scale Image Retrieval

Color-Based Large-Scale Image Retrieval with Limited Hardware Resources

2016 ◽  
pp. 689-699
Author(s):  
Michał Łagiewka ◽  
Rafał Scherer ◽  
Rafal Angryk
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Large Scale Image Retrieval

A Combination of Spatial Pyramid and Inverted Index for Large-Scale Image Retrieval

2018 ◽  
pp. 1307-1321
Author(s):  
Vinh-Tiep Nguyen ◽  
Thanh Duc Ngo ◽  
Minh-Triet Tran ◽  
Duy-Dinh Le ◽  
Duc Anh Duong
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Spatial Information ◽  
Real Life ◽  
Inverted Index ◽  
Bag Of Words ◽  
Visual Words ◽  
Benchmark Datasets ◽  
Large Scale Image Retrieval ◽  
Inverted Indexing

Large-scale image retrieval has been shown remarkable potential in real-life applications. The standard approach is based on Inverted Indexing, given images are represented using Bag-of-Words model. However, one major limitation of both Inverted Index and Bag-of-Words presentation is that they ignore spatial information of visual words in image presentation and comparison. As a result, retrieval accuracy is decreased. In this paper, the authors investigate an approach to integrate spatial information into Inverted Index to improve accuracy while maintaining short retrieval time. Experiments conducted on several benchmark datasets (Oxford Building 5K, Oxford Building 5K+100K and Paris 6K) demonstrate the effectiveness of our proposed approach.

A Combination of Spatial Pyramid and Inverted Index for Large-Scale Image Retrieval

2015 ◽  
Vol 6 (2) ◽  
pp. 37-51 ◽  
Author(s):  
Vinh-Tiep Nguyen ◽  
Thanh Duc Ngo ◽  
Minh-Triet Tran ◽  
Duy-Dinh Le ◽  
Duc Anh Duong
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Spatial Information ◽  
Real Life ◽  
Inverted Index ◽  
Bag Of Words ◽  
Visual Words ◽  
Benchmark Datasets ◽  
Large Scale Image Retrieval ◽  
Inverted Indexing

Large-scale image retrieval has been shown remarkable potential in real-life applications. The standard approach is based on Inverted Indexing, given images are represented using Bag-of-Words model. However, one major limitation of both Inverted Index and Bag-of-Words presentation is that they ignore spatial information of visual words in image presentation and comparison. As a result, retrieval accuracy is decreased. In this paper, the authors investigate an approach to integrate spatial information into Inverted Index to improve accuracy while maintaining short retrieval time. Experiments conducted on several benchmark datasets (Oxford Building 5K, Oxford Building 5K+100K and Paris 6K) demonstrate the effectiveness of our proposed approach.

scholarly journals Online Supervised Sketching Hashing for Large-Scale Image Retrieval

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 88369-88379 ◽  
Author(s):  
Zhenyu Weng ◽  
Yuesheng Zhu
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Large Scale Image Retrieval
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