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Bundle min-hashing for logo recognition

Stefan Romberg, Rainer Lienhart
2013 Proceedings of the 3rd ACM conference on International conference on multimedia retrieval - ICMR '13  
We present a scalable logo recognition technique based on feature bundling. Individual local features are aggregated with features from their spatial neighborhood into bundles.  ...  We demonstrate the benefits of these techniques for both small object retrieval and logo recognition.  ...  Inspired by this observation we exploit a feature bundling technique that builds on visual words, but aggregates spatial neighboring visual words into feature bundles.  ... 
doi:10.1145/2461466.2461486 dblp:conf/mir/RombergL13 fatcat:tcio7g3mwfedrkq26l4fwgywmu

Robust Feature Bundling [chapter]

Stefan Romberg, Moritz August, Christian X. Ries, Rainer Lienhart
2012 Lecture Notes in Computer Science  
In this work we present a feature bundling technique that aggregates individual local features with features from their spatial neighborhood into bundles.  ...  We demonstrate the benefits of these bundles for small object retrieval, i.e. logo recognition, and generic image retrieval.  ...  visual words into feature bundles.  ... 
doi:10.1007/978-3-642-34778-8_5 fatcat:om2c6oqllfbwxpberdodsswibm

Bundle min-Hashing

Stefan Romberg, Rainer Lienhart
2013 International Journal of Multimedia Information Retrieval  
We present a feature bundling technique based on min-Hashing. Individual local features are aggregated with features from their spatial neighborhood into bundles.  ...  We demonstrate the benefits of these techniques for both small object retrieval and logo recognition.  ...  It does not describe each visual word individually but rather aggregates spatial neighboring visual words into feature bundles.  ... 
doi:10.1007/s13735-013-0040-x fatcat:3jzzxkfvnjbizieidjusag2kyu

Predicting Good Features for Image Geo-Localization Using Per-Bundle VLAD

Hyo Jin Kim, Enrique Dunn, Jan-Michael Frahm
2015 2015 IEEE International Conference on Computer Vision (ICCV)  
Also, for both learning to predict features and retrieving geo-tagged images from the database, we propose per-bundle vector of locally aggregated descriptors (PBVLAD), where each maximally stable region  ...  is described by a vector of locally aggregated descriptors (VLAD) on multiple scale-invariant features detected within the region.  ...  The authors would also like to thank Alex Berg and Amir Zamir for helpful discussions.  ... 
doi:10.1109/iccv.2015.139 dblp:conf/iccv/KimDF15 fatcat:f74k7gpmqvfb3k6f74ch5jg5he

Recent Advance in Content-based Image Retrieval: A Literature Survey [article]

Wengang Zhou, Houqiang Li, Qi Tian
2017 arXiv   pre-print
Numerous techniques have been developed for content-based image retrieval in the last decade.  ...  With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content.  ...  Feature Aggregation When an image is represented by a set of local features, it is necessary to aggregate those local features into a fixedlength vector representation for convenience of similarity comparison  ... 
arXiv:1706.06064v2 fatcat:m52xwsw5pzfzdbxo5o6dye2gde

MorphoCluster: Efficient Annotation of Plankton images by Clustering [article]

Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
2020 arXiv   pre-print
By sorting a set of 1.2M objects into 280 data-driven classes in 71 hours (16k objects per hour), with 90% of these classes having a precision of 0.889 or higher.  ...  By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator and allows experts to adapt the granularity of their  ...  Acknowledgments: We thank Svenja Christiansen, Jean-Olivier Irisson and Marc Picheral for insightful discussions on plankton image sorting.  ... 
arXiv:2005.01595v1 fatcat:p6cki22y35dmbpjx54nlpr2c3a

A Novel Feature Aggregation Approach for Image Retrieval Using Local and Global Features

Yuhua Li, Zhiqiang He, Junxia Ma, Zhifeng Zhang, Wangwei Zhang, Prasenjit Chatterjee, Dragan Pamucar
2022 CMES - Computer Modeling in Engineering & Sciences  
To solve the problem, we propose a new image retrieval method that employs a novel feature aggregation approach with an attention mechanism and utilizes a combination of local and global features.  ...  The core of the aggregation mechanism is to allow features with high scores to participate in residual operations of all cluster centers.  ...  For performance evaluation, we used Precision-Recall curve, while taking into account all the query images.  ... 
doi:10.32604/cmes.2022.016287 fatcat:dtsswsthnvak7noirxjhxmwvp4

Mini-Batch VLAD for Visual Place Retrieval

Reem Aljuaidi, Jing Su, Rozenn Dahyot
2019 2019 30th Irish Signals and Systems Conference (ISSC)  
Vector of Locally Aggregated Descriptors (VLAD) is one of the local features that can be used for image place recognition.  ...  VLAD describes an image by the difference of its local feature descriptors from an already computed codebook. Generally, a visual codebook is generated from k-means clustering of the descriptors.  ...  ACKNOWLEDGMENTS This work is partly funded by Prince Sattam bin Abdalaziz University Scholarship Program from Saudi Arabian Government, and the ADAPT Centre for Digital Content Technology  ... 
doi:10.1109/issc.2019.8904931 fatcat:cd7rzsqof5d3bnj4oq2rwjzaha

Large scale partial-duplicate image retrieval with bi-space quantization and geometric consistency

Wengang Zhou, Houqiang Li, Yijuan Lu, Qi Tian
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
The state-of-the-art image retrieval approaches represent image with a high dimensional vector of visual words by quantizing local features, such as SIFT, solely in descriptor space.  ...  Local features are quantized to visual words first in descriptor space and then in orientation space. Moreover, geometric consistency constraints are embedded into the relevance formulation.  ...  In [8] , two geometric inconsistency terms, ) ; ( p q M X and ) ; ( p q M Y denoting the geometric inconsistency order in X-and Y-coordinates respectively, are defined for local bundling feature.  ... 
doi:10.1109/icassp.2010.5496205 dblp:conf/icassp/ZhouLLT10 fatcat:ca7o75gu6rcxtjlh5vzntu3z2m

Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods

Ferdinand Maiwald, Christoph Lehmann, Taras Lazariv
2021 ISPRS International Journal of Geo-Information  
Results show that image retrieval approaches outperform the metadata search and are a valuable strategy for finding images of interest.  ...  Finally, the combination of a CNN-based image retrieval and the feature matching methods SuperGlue and DISK show very promising results to realize a fully automated workflow.  ...  Such a single PR curve is aggregated into one number by averaging the precision values along the curve, that leads to average precision (AP) ranging in the unit interval [0, 1].  ... 
doi:10.3390/ijgi10110748 fatcat:l2lhld6tevhizixrxbq2rvdvau

A survey on Visual-Based Localization: On the benefit of heterogeneous data

Nathan Piasco, Désiré Sidibé, Cédric Demonceaux, Valérie Gouet-Brunet
2018 Pattern Recognition  
Finally, we conclude the paper with a discussion on promising trends that could permit to a localization system to reach high precision pose estimation within an area as large as possible.  ...  We start by categorizing VBL methods into two distinct families: indirect and direct localization systems.  ...  Acknowledgements We would like to acknowledge the French ANR project pLaTINUM (ANR-15-CE23-0010) for its financial support.  ... 
doi:10.1016/j.patcog.2017.09.013 fatcat:adelbfkxgfd3xik6f7fubv32mu

Reuse your features: unifying retrieval and feature-metric alignment [article]

Javier Morlana, J.M.M. Montiel
2022 arXiv   pre-print
DRAN is the first single network able to produce the features for the three steps of visual localization.  ...  Our DRAN (Deep Retrieval and image Alignment Network) is able to extract global descriptors for efficient image retrieval, use intermediate hierarchical features to re-rank the retrieval list and produce  ...  Images are translated into compact vectors based on the deepest features, which typically encodes the high-level features of the image.  ... 
arXiv:2204.06292v1 fatcat:ux7w27zmivd7jfxzzdxhog4fg4

Spatial coding for large scale partial-duplicate web image search

Wengang Zhou, Yijuan Lu, Houqiang Li, Yibing Song, Qi Tian
2010 Proceedings of the international conference on Multimedia - MM '10  
The state-of-the-art image retrieval approaches represent images with a high dimensional vector of visual words by quantizing local features, such as SIFT, in the descriptor space.  ...  Our spatial coding is both efficient and effective to discover false matches of local features between images, and can greatly improve retrieval performance.  ...  In [8] , Bundled-feature groups features in local MSER [12] regions into a local group to increase the discriminative power of local features.  ... 
doi:10.1145/1873951.1874019 dblp:conf/mm/ZhouLLST10 fatcat:bw2xxhu425garb3q5he5r7a4fy

Instance search retrospective with focus on TRECVID

George Awad, Wessel Kraaij, Paul Over, Shin'ichi Satoh
2017 International Journal of Multimedia Information Retrieval  
the small world of the BBC Eastenders series for the last 3 years.  ...  This paper presents an overview of the Video Instance Search benchmark which was run over a period of 6 years (2010-2015) as part of the TREC Video Retrieval (TRECVID) workshop series.  ...  Bundled features [73] uses a similar idea: bundle multiple interest points in a local neighborhood, use them together to describe the region, and incorporate them into an inverted file.  ... 
doi:10.1007/s13735-017-0121-3 pmid:28758054 pmcid:PMC5531298 fatcat:3khp2cscmbhohipfx246gspqlq

A P2P Platform for Collaborative Aggregated Multimedia Sharing

Ines Fakhfakh, Hongguang Zhang, Marc Girod-Genet
2013 Communications and Network  
To overcome these shortcomings, we elaborated a reference model of P2P architecture for a dynamic aggregation, sharing and retrieval of heterogeneous multimedia contents (simple or aggregated).  ...  In this paper, we detail and evaluate an original semantic-based community network architecture for heterogeneous multimedia content sharing and retrieval.  ...  For the same result, we calculate the search time needed by the system to retrieve bundles based on different keywords.  ... 
doi:10.4236/cn.2013.53b2097 fatcat:vzfuw7ybt5hkfb55untfyqgxru
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