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Fusing Local Image Descriptors for Large-Scale Image Retrieval

Eva Horster, Rainer Lienhart
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
Here we will employ the image content as a source of information to retrieve images and study the representation of images by topic models for content-based image retrieval.  ...  Therefore, we also investigate which visual descriptor (set) is most appropriate for each of the twelve classes under consideration.  ...  In previous work [9] the authors investigated three techniques for learning visual words from local image features for large-scale image databases.  ... 
doi:10.1109/cvpr.2007.383490 dblp:conf/cvpr/HorsterL07 fatcat:arm3opexqnhrph2lteel4r6tfe

Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers [article]

Christof Henkel
2021 arXiv   pre-print
We show how to combine and enhance concepts from recent research in image retrieval and introduce two architectures especially suited for large-scale landmark identification.  ...  Furthermore, we elaborate a novel discriminative re-ranking methodology for image retrieval.  ...  Conclusion We presented several improvements to previous approaches for large-scale landmark identification leading to winning both tracks of the 2021 Google landmark competition.  ... 
arXiv:2110.03786v2 fatcat:rzgx7twnifftrabmq6nkuk6uya

Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

Chang Che, Xiaoyang Yu, Xiaoming Sun, Boyang Yu
2017 EURASIP Journal on Advances in Signal Processing  
Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision.  ...  We conducted intensive experiments on small-scale to large-scale image datasets: , where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and  ...  In addition to the new distance metric, a new framework is proposed for large-scale image retrieval which can fuse matching results from different image representation methods.  ... 
doi:10.1186/s13634-017-0456-1 fatcat:dzrrvko55jdcpe7zdfzfjnoiiu

Fusion of Deep Features and Weighted VLAD Vectors based on Multiple Features for Image Retrieval

Yanhong. Wang, Yigang. Cen, Liequan. Liang, Linna. Zhang, Viacheslav. Voronin, Vladimir. Mladenovic, T. Abbasian Najafabadi, I. Sevostianov, K. Yeghiazaryan, A. Nguyen Dong, V. Mladenovic
2017 MATEC Web of Conferences  
Also, in order to reduce running time and improve retrieval accuracy, PCA and whitening operations are used for VLAD vectors.  ...  Moreover, we fuse deep features and the multiple VLAD vectors based on local gradient and color information.  ...  Science Foundation of China (61611530710); Beijing Municipal Natural Science Foundation (4162050); The Natural Science Foundation of Guangdong Province (2016A030313708) and the Fundamental Research Funds for  ... 
doi:10.1051/matecconf/201713205002 fatcat:wulpkq6ydjao5eucrfkobx5vra

Distribution Entropy Boosted VLAD for Image Retrieval

Qiuzhan Zhou, Cheng Wang, Pingping Liu, Qingliang Li, Yeran Wang, Shuozhang Chen
2016 Entropy  
Several recent works have shown that aggregating local descriptors to generate global image representation results in great efficiency for retrieval and classification tasks.  ...  We present a novel image presentation called Distribution Entropy Boosted VLAD (EVLAD), which extends the original vector of locally aggregated descriptors.  ...  Large-Scale Image Retrieval We use Holiday to evaluate the performance of large-scale image retrieval.  ... 
doi:10.3390/e18080311 fatcat:sih3ua4zfzhmtocfr3uipcob4u

Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition

Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer
2021 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
This paper introduces Patch-NetVLAD, which provides a novel formulation for combining the advantages of both local and global descriptor methods by deriving patch-level features from NetVLAD residuals.  ...  We further introduce a multi-scale fusion of patch features that have complementary scales (i.e. patch sizes) via an integral feature space and show that the fused features are highly invariant to both  ...  Acknowledgements: We would like to thank Gustavo Carneiro and Niko Suenderhauf for their valuable comments in preparing this paper.  ... 
doi:10.1109/cvpr46437.2021.01392 fatcat:rsarcdwqmbewbh6xypl3yart6u

Enhancement of Image Retrieval by Using Colour, Texture and Shape Features

Apurva N. Ganar, C.S. Gode, Sachin M. Jambhulkar
2014 2014 International Conference on Electronic Systems, Signal Processing and Computing Technologies  
For the cooccurrence matrix between the local image and the images in the database to retrieve the image. For extracting shape feature gradient method is used here.  ...  Based on this principle, CBIR system uses color, texture and shape fused features to retrieve desired image from the large database and hence provides more efficiency or enhancement in image retrieval  ...  for image retrieval to enhance the image retrieval results to a better efficiency.  ... 
doi:10.1109/icesc.2014.48 fatcat:xom222duzjdxpf2hgxs5jfgorq

Bag of Visual Words Techniques for Content- Based Image Retrieval and the Role Using in Computer Vision Major: A Survey

Abdullah MMA Al-Omari, Abdullah Noman
2021 Zenodo  
Nowadays, Content-Based Image Retrieval (CBIR) became an active research field, to produce typical solutions for similar images retrieval from image databases.  ...  Also, the need for accurate image retrieval is forced to development of more efficient methods.  ...  Next, I would like to thank my advisor, professor Fan Xiangxiang, for his assistance and followup throughout our work.  ... 
doi:10.5281/zenodo.5448762 fatcat:go4qzq6ktrcp5d6nvs7royxokm

Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

S. Balammal@Geetha, R. Muthukkumar, V. Seenivasagam
2022 Intelligent Automation and Soft Computing  
The fusion of local feature descriptor and global feature descriptor boost the retrieval of images having diverse semantic classification and also helps in achieving the better results in large scale retrieval  ...  The fusion of local and global feature representations are selected for image retrieval for the reason that SIFT effectively captures shape and texture and robust towards the change in scale and rotation  ...  [36] presented a retrieval system that uses the local feature descriptors SIFT and SURF along with BoVW for efficient image retrieval.  ... 
doi:10.32604/iasc.2022.018822 fatcat:udowuyfkajcwtnsbiffbsar5ju

DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features [article]

Min Yang, Dongliang He, Miao Fan, Baorong Shi, Xuetong Xue, Fu Li, Errui Ding, Jizhou Huang
2021 arXiv   pre-print
Specifically, we propose a Deep Orthogonal Local and Global (DOLG) information fusion framework for end-to-end image retrieval.  ...  A common image retrieval practice is to firstly retrieve candidate images via similarity search using global image features and then re-rank the candidates by leveraging their local features.  ...  Among these methods, the state-of-the-art local feature learning framework DELF [29] , which proposes an attentive local feature descriptor for large-scale image retrieval, is closely related to our work  ... 
arXiv:2108.02927v2 fatcat:goywykicubgaxo3ypommsoesc4

Fusing Feature Distribution Entropy with R-MAC Features in Image Retrieval

Pingping Liu, Guixia Gou, Huili Guo, Danyang Zhang, Hongwei Zhao, Qiuzhan Zhou
2019 Entropy  
We propose a novel pooling method, which fuses our proposed FDE with region maximum activations of convolutions (R-MAC) features to improve the performance of image retrieval, as it takes the advantage  ...  The pooling method has become a research hotpot in the task of image retrieval in recent years.  ...  ] for large-scale image retrieval.  ... 
doi:10.3390/e21111037 fatcat:a3kpbgfy5jdkjntyw57cf7wxk4

Accurate Visual Localization for Automotive Applications [article]

Eli Brosh, Matan Friedmann, Ilan Kadar, Lev Yitzhak Lavy, Elad Levi, Shmuel Rippa, Yair Lempert, Bruno Fernandez-Ruiz, Roei Herzig, Trevor Darrell
2019 arXiv   pre-print
As a benchmark to evaluate the performance of our visual localization approach, we introduce a new large-scale driving dataset based on video and GPS data obtained from a large-scale network of connected  ...  This representation enables efficient visual retrieval and provides coarse localization cues, which are fused with vehicle ego-motion to obtain high accuracy location estimates.  ...  layers as local features that can be aggregated into a descriptor suitable for image retrieval [4, 31] .  ... 
arXiv:1905.03706v1 fatcat:zcudnfk2bjehje77kdfyay2xty

Human-centric approaches to image understanding and retrieval

Rui Li, Preethi Vaidyanathan, Sai Mulpuru, Jeff Pelz, Pengcheng Shi, Cara Calvelli, Anne Haake
2010 2010 Western New York Image Processing Workshop  
A key goal of recent researches on image retrieval is to develop retrieval systems that respond to individual user's query for real time applications.  ...  This paper reports on the recent trends in Content Based Image Retrieval approaches and their resolved issues.  ...  Hybrid features include has been derived using mutual information descriptors various combinations like Color fused texture feature, (MIDs) and the self information descriptors (SIDs) for Color fused Shape  ... 
doi:10.1109/wnyipw.2010.5649743 fatcat:tej3mc24ffgppa7aop4ea5qmku

Object Retrieval and Localization in Large Art Collections Using Deep Multi-style Feature Fusion and Iterative Voting [chapter]

Nikolai Ufer, Sabine Lang, Björn Ommer
2020 Lecture Notes in Computer Science  
Computer vision has presented efficient methods for visual instance retrieval across photographs.  ...  In this paper, we present a multi-style feature fusion approach that successfully reduces the domain gap and improves retrieval results without labelled data or curated image collections.  ...  In this work, we focus on large-scale instance retrieval and localization in the arts.  ... 
doi:10.1007/978-3-030-66096-3_12 fatcat:vuzaj75zibfmjomgjrpbxusvnm

Learning Multi-view Deep Features for Small Object Retrieval in Surveillance Scenarios

Haiyun Guo, Jinqiao Wang, Min Xu, Zheng-Jun Zha, Hanqing Lu
2015 Proceedings of the 23rd ACM international conference on Multimedia - MM '15  
objects of interest in a large-scale dataset.  ...  Then, the complementary multi-view deep features are encoded into short binary codes by Locality-Sensitive Hash (LSH) and fused to retrieve objects.  ...  For searching objects in large scale dataset, high dimensionality will significantly corrupt the retrieval efficiency.  ... 
doi:10.1145/2733373.2806349 dblp:conf/mm/GuoWXZL15 fatcat:7gzu3u7yizbihdb4cofff423la
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