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Randomized Locality Sensitive Vocabularies for Bag-of-Features Model
[chapter]
2010
Lecture Notes in Computer Science
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Visual vocabulary construction is an integral part of the popular Bag-of-Features (BOF) model. ...
In this paper we propose the random locality sensitive vocabulary (RLSV) scheme towards efficient visual vocabulary construction in such scenarios. ...
Introduction The bag-of-features (BOF) model (also known as the bag-of-words) has gained much empirical success in producing orderless representations of feature-rich vision data. ...
doi:10.1007/978-3-642-15558-1_54
fatcat:6ynd25pzmfapjhi7kl4v72f53i
Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features
2009
Proceeding of the ACM International Conference on Image and Video Retrieval - CIVR '09
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To efficiently compare among large sets of local features, the algorithm employs bag-of-features approach to integrate the local features into a feature vector per model. ...
Our previous shape-based 3D model retrieval algorithm compares 3D shapes by using thousands of local visual features per model. ...
This research has been funded in part by the Ministry of Education, Culture, Sports, Sciences, and Technology of Japan (No. 17500066 and No. 18300068). ...
doi:10.1145/1646396.1646430
dblp:conf/civr/FuruyaO09
fatcat:ih4oak5ofnclnjgwzb6rmhsxxe
Image Retrieval based on Bag-of-Words model
[article]
2013
arXiv
pre-print
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This article gives a survey for bag-of-words (BoW) or bag-of-features model in image retrieval system. ...
We call this model as bag-of-words or bag-of-features model. ...
To further improve the performance of BoW, we also introduce the idea of incorporating spatial information, combining BoW model with global features and query expansion. ...
arXiv:1304.5168v1
fatcat:6jycm42bg5guzgzlzdbc2pydby
Visual synonyms for landmark image retrieval
2012
Computer Vision and Image Understanding
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In this paper, we address the incoherence problem of the visual words in bag-of-words vocabularies. ...
We show that visual synonyms may successfully be used for vocabulary reduction. ...
Under the bag-of-words model each visual word w j covers a sensitive subspace F w j in descriptor space F . ...
doi:10.1016/j.cviu.2011.10.004
fatcat:d4nuvyflhfde7hoshaiezukgvq
Introduction to the Bag of Features Paradigm for Image Classification and Retrieval
[article]
2011
arXiv
pre-print
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The past decade has seen the growing popularity of Bag of Features (BoF) approaches to many computer vision tasks, including image classification, video search, robot localization, and texture recognition ...
Among the unresolved issues are determining the best techniques for sampling images, describing local image features, and evaluating system performance. ...
BAG OF FEATURES IMAGE REPRESENTATION A Bag of Features method is one that represents images as orderless collections of local features. ...
arXiv:1101.3354v1
fatcat:bmiomdpje5fhlfrzrlhhhpvt3u
Image Classification Using Bag of Visual Words (BoVW)
2018
Al-Nahrain Journal of Science
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Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new ...
unlabeled image using nearest neighbor classification method for features descriptor. ...
The information that extracted in the first stage used to classify new unlabeled image based on bag of features created using supervised BoVW approach on set of training images. ...
doi:10.22401/anjs.21.4.11
fatcat:fpj3tpwhnbd5fh2fkm3kiofcey
k-mer grammar uncovers maize regulatory architecture
[article]
2017
bioRxiv
pre-print
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The models learn to classify regulatory regions based on sequence features -k-mers. ...
To do this, we borrowed two approaches from the field of natural language processing: (1) "bag-of-words" which is commonly used for differentially weighting key words in tasks like sentiment analyses, ...
To obtain a global view of how many k-mers are embedded in different local sequences between regulatory and random regions, we collected for any given k-mer (k=8) in the vocabulary, the list of the closest ...
doi:10.1101/222927
fatcat:ekotqw54xvbpnjc5sk6nvlk7uq
An AES-Based Secure Image Retrieval Scheme Using Random Mapping and BOW in Cloud Computing
2020
IEEE Access
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It is a ciphertext image retrieval method based on random mapping features with the bag-of-words model. ...
INDEX TERMS Image retrieval, AES encryption, BOW model, random mapping. ...
ACKNOWLEDGMENT The authors would like to thank the Editor and the Anonymous Reviewers for their constructive comments and suggestions, which improve the quality of this article. ...
doi:10.1109/access.2020.2983194
fatcat:gdy6h7sy4rbkjjvoqa7cczsf4m
Change Detection under Global Viewpoint Uncertainty
[article]
2017
arXiv
pre-print
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the recently developed Bag-of-Local-Convolutional-Features (BoLCF) scene model. 3) Change detection is reformulated as a scene retrieval over these reference images to find changed objects using a novel ...
spatial Bag-of-Words (SBoW) scene model. ...
Middle: Bag-of-local-convolutional-features (BoLCF) histogram for query and top-ranked reference images for the first row. ...
arXiv:1703.00552v1
fatcat:hfeasmiclrcbjo5uc6koc76wo4
Shape google
2011
ACM Transactions on Graphics
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We also show that considering pairs of "geometric words" ("geometric expressions") allows creating spatially-sensitive bags of features with better discriminative power. ...
These methods allow representing images as collections of "visual words" and treat them using text search approaches following the "bag of features" paradigm. ...
Acknowledgment We are grateful to Zhouhui Lian and Umberto Castellani for providing the performance of their algorithms on the SHREC'10 benchmark, and to Giuseppe Patané for providing the FEM computation ...
doi:10.1145/1899404.1899405
fatcat:rwtead35svcmrplfxr3lfmtz6a
Object identification with tactile sensors using bag-of-features
2009
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
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We apply a bag-of-words approach for object identification. ...
The histogram codebook models distributions over the vocabulary and is the core identification mechanism. ...
The key idea of the bag-of-features approach is to describe the observations with a common vocabulary of features. ...
doi:10.1109/iros.2009.5354648
dblp:conf/iros/SchneiderSSRBB09
fatcat:cubvcd2o7rdgpaav23qo6xz3vi
Fuzzy indexing for Bag of Features scene categorization
2010
2010 5th International Symposium On I/V Communications and Mobile Network
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This paper presents a novel Bag of Features (BoF) method for image classification. ...
The BoF approach describes an image as a set of local descriptors using a histogram, where each bin represents the importance of a visual word. ...
E xtracting Local Features A very interesting approach for extracting local features is to detect keypoints. Those are the centers of salient patches generally located around the corners and edges. ...
doi:10.1109/isvc.2010.5656164
fatcat:b264x2izincnppi5nwzvv7dbii
A k-mer grammar analysis to uncover maize regulatory architecture
2019
BMC Plant Biology
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The models learn to classify regulatory regions based on sequence features -k-mers. ...
To do this, we borrowed two approaches from the field of natural language processing: (1) "bag-of-words" which is commonly used for differentially weighting key words in tasks like sentiment analyses, ...
Acknowledgements We thank to the members of the Buckler lab for comments that greatly improved the manuscript. Specially to Sara Miller for her assistance in language editing, and proofreading. ...
doi:10.1186/s12870-019-1693-2
fatcat:hlnp6b2nc5bahbmlwj7bk6ut6u
Bundle min-hashing for logo recognition
2013
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval - ICMR '13
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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. ...
Min-hashing (mH) Min-Hashing is a locality-sensitive hashing technique that allows for approximate similarity search of sparse sets. It models an image as a sparse set of visual word occurrences. ...
doi:10.1145/2461466.2461486
dblp:conf/mir/RombergL13
fatcat:tcio7g3mwfedrkq26l4fwgywmu
Bag of Features (BoF) Based Deep Learning Framework for Bleached Corals Detection
2021
Big Data and Cognitive Computing
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In this paper, we propose a bag of features (BoF) based approach that can detect and localize the bleached corals before the safety measures are applied. ...
binary pattern are used for feature extraction. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/bdcc5040053
fatcat:qqjirp6njjcrrko6unnb6pfwwy
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