A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Image Retrieval based on VA-File and Multi-Resolution BOW
2015
Applied Mathematics & Information Sciences
Preserved Fulltext
Based on stratified construction, we have improved uniform quantization multi-resolution BOF and proposed a non-linear Non-uniform quantization multi-resolution BOF method, which is combined with VA-file ...
By the virtue of BOF to describe high-dimensional data, in this article, we propose an effective retrieval strategy employing multi-resolution BOF to accelerate the match. ...
Descriptive features of images Image features consist of global features and local features. Global features describe colors, textures, shapes, greyness coexistence matrixes and so on. ...
doi:10.12785/amis/010152
fatcat:rqt3abnucvbkhmzu7vbsgmdsmq
Image Retrieval based on VA-File and Multi-Resolution BOW
2015
Applied Mathematics & Information Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Based on stratified construction, we have improved uniform quantization multi-resolution BOF and proposed a non-linear Non-uniform quantization multi-resolution BOF method, which is combined with VA-file ...
By the virtue of BOF to describe high-dimensional data, in this article, we propose an effective retrieval strategy employing multi-resolution BOF to accelerate the match. ...
Descriptive features of images Image features consist of global features and local features. Global features describe colors, textures, shapes, greyness coexistence matrixes and so on. ...
doi:10.12785/amis/090152
fatcat:z2q5yfftqrdxji4q2l5cw6iv2a
Introduction to the Bag of Features Paradigm for Image Classification and Retrieval
[article]
2011
arXiv
pre-print
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
Despite this, or perhaps because of this, BoF-based systems have set new performance standards on popular image classification benchmarks and have achieved scalability breakthroughs in image retrieval. ...
BoF methods are based on orderless collections of quantized local image descriptors; they discard spatial information and are therefore conceptually and computationally simpler than many alternative methods ...
A Bag of Features based image retrieval algorithm returns results based on a similarity score (distance) between the query image term vector and the term vectors of the gallery images, ranked accordingly ...
arXiv:1101.3354v1
fatcat:bmiomdpje5fhlfrzrlhhhpvt3u
Recognition of Arabic Handwritten Words using Gabor-based Bag-of-Features Framework
2018
International Journal of Computing and Digital Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
A handwritten text image is filtered by a set of Gabor filters of different scales and orientations for extracting texture-based local features. ...
In this work we present a system for the automatic recognition of Arabic handwritten words based on statistical features extracted by Bag-of-Features framework that exploits the discriminative power of ...
The BoF framework encodes the local features of text images in robust statistical features that are fed to the classifier as a representation for the images. ...
doi:10.12785/ijcds/070104
fatcat:y7kahbbzzjb6lbfd6m5ze5t34u
Mean BoF per Quadrant - Simple and Effective Way to Embed Spatial Information in Bag of Features
2015
Proceedings of the 10th International Conference on Computer Vision Theory and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The method is conceptually related to Spatial Pyramids but instead of requiring fixed and arbitrary sub-regions where to compute region-based BoF, it relies on an adaptive procedure based on multiple partitioning ...
of the image in four quadrants (the NE, NW, SE, SW regions of the image). ...
Figure 1 : 1 Image representation based on MBoFQ approach. A dense grid of local features is considered (left). ...
doi:10.5220/0005281002970304
dblp:conf/visapp/Sosa-GarciaO15
fatcat:2xjzyz5nvvapha5gggpaihrjqm
Pairwise geometric matching for large-scale object retrieval
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Spatial verification is a key step in boosting the performance of object-based image retrieval. ...
It serves to eliminate unreliable correspondences between salient points in a given pair of images, and is typically performed by analyzing the consistency of spatial transformations between the image ...
This representation typically involves detection of salient points in the image and representation of these points by suitable feature vectors describing local image regions around these points. ...
doi:10.1109/cvpr.2015.7299151
dblp:conf/cvpr/LiLH15
fatcat:enjbpf25rzb6xewusogiwxn4mm
Pattern Classification of Melanoma by Local Features Using BoF Based Spatial Encoding
2017
International Journal of Engineering and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Scale invariant Speeded up Robust Features (SURF) technique is used for feature point detection in Low Level Image representation. ...
In this paper, Bag of Features based Supervised Spatial Encoding of Feature extraction is proposed. Low Level Images and their Latent Features induce codebook of features. ...
For sliding window consisting of k= regions { , … … represents BoF of sliding window regions, vector denotes concatenation of its feature vector (FV) as: , … … (1) Where | | is the BoF representation of ...
doi:10.21817/ijet/2017/v9i6/170906115
fatcat:3rmbtgw5yvbczl3xg2gg3u63w4
Exploring self-similarities of bag-of-features for image classification
2011
Proceedings of the 19th ACM international conference on Multimedia - MM '11
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The use of bag-of-features (BOF) models has been a popular technique for image classification and retrieval. ...
The proposed self-similarity hypercubes (SSH) model, which observes the concurrent occurrences of visual words in an image, is able to describe the structural information of the BOF in an image. ...
Acknowledgements This work is supported in part by the National Science Council of Taiwan via NSC 100-2221-E-001-018-MY2 and NSC 100-2631-H-001-013. ...
doi:10.1145/2072298.2072030
dblp:conf/mm/ChenW11
fatcat:gqstjeufnvd2zh7374nspgy4oy
Multiple Models Fusion for Emotion Recognition in the Wild
2015
Proceedings of the 2015 ACM on International Conference on Multimodal Interaction - ICMI '15
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
For dense SIFT features, we use the bag of features (BoF) model with two different encoding methods (locality-constrained linear coding and group saliency based coding) to further represent it. ...
By learning the optimal weight of each model based on the regression value, we fuse these models together. ...
We adopt max pooling [31] in this paper. By pooling code vectors in each spatial subregion across different spatial scales, we obtain the local description of every block. ...
doi:10.1145/2818346.2830582
dblp:conf/icmi/WuLZ15
fatcat:xmjm7omlqvghtfcj4ykkfnn7ca
Single sample face recognition via BoF using multistage KNN collaborative coding
2019
Multimedia tools and applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this paper, we propose a multistage KNN collaborative coding based Bag-of-Feature (MKCC-BoF) method to address SSPP problem, which tries to weaken the semantic gap between facial features and facial ...
Finally, a SVM classifier based on linear kernel is trained with the concatenated features from pooling results. ...
Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ...
doi:10.1007/s11042-018-7002-5
fatcat:5dn2e65r5ngj5eadn4enapgf4e
Weakly supervised sparse coding with geometric consistency pooling
2012
2012 IEEE Conference on Computer Vision and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is application/pdf.
As an effect, local descriptors enjoying good geometric consistency are pooled together to ensure a more precise spatial layouts embedding in BoF. ...
But still, much information has been discarded by quantizing local descriptors with twodimensional layouts into a one-dimensional BoF histogram. ...
Based on the quantitative evaluations in the image classification on Scene15 and Cal-tech256 benchmarks, as well as the image search on large scale Holiday1M and NUS-WIDE benchmarks, our "WSC + GCP" based ...
doi:10.1109/cvpr.2012.6248102
dblp:conf/cvpr/CaoJGYT12
fatcat:tpgmreckkjfmhdzmzc3fsvqhtm
A Fast Table-Based Approach of Bag-of-Features for Large-Scale Image Classification
2015
Proceedings of the ITE Annual Convention
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
For large-scale image classification problems, feature extraction has been one of the most time-consuming parts. ...
This paper introduces a table-based method of finding bag-of-features-based indexes of query pictures without feature extraction. ...
The proposed look-up table created by local patches and their corresponding visual words is used to find BoF-based indexes of query images. ...
doi:10.11485/iteac.2015.0_24a-1
fatcat:b7bqqbouynfivgfgqgmwfhnaee
Non-rigid 3D shape retrieval using Multidimensional Scaling and Bag-of-Features
2010
2010 IEEE International Conference on Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Then, each image is described as a word histogram obtained by the vector quantization of the image's salient local features. ...
Index Terms-3D shape retrieval, Non-rigid 3D shape, Multidimensional Scaling (MDS), Bag-of-Features (BOF) ...
Since our method is mainly based on Multidimensional Scaling, Clock Matching, and Bag-of-Features, for the sake of convenience, we denote the algorithm as "MDS-CM-BOF". ...
doi:10.1109/icip.2010.5654226
dblp:conf/icip/LianGSZ10
fatcat:jffbfcq3dnfbxax4vzfahelbpy
On Reducing the Number of Visual Words in the Bag-of-Features Representation
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We show that very relevant improvement in performance are achievable still preserving the advantages of the BoF base approach. ...
The state-of-the-art algorithms for large visual content recognition and content based similarity search today use the "Bag of Features" (BoF) or "Bag of Words" (BoW) approach. ...
Please note that the scale threshold is not defined a priori but it depends on the number of local features actually extracted from the image. • tf -During the BoF words assignment phase, each local feature ...
arXiv:1604.04142v1
fatcat:kgmcgxrc7bdh7g22r6ps5ospgy
Large-scale multimedia data mining using MapReduce framework
2012
4th IEEE International Conference on Cloud Computing Technology and Science Proceedings
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, the framework of MapReduce is explored for large-scale multimedia data mining. ...
Experimental results on image classification, video event detection and near-duplicate video retrieval are carried out on a five-node Hadoop cluster to demonstrate the efficiency of the proposed MapReduce ...
Finally, the BoF-based feature vectors and labels of the training samples are input to classifiers such as the Support Vector Machine (SVM) to generate the prediction model for image classification and ...
doi:10.1109/cloudcom.2012.6427595
dblp:conf/cloudcom/WangSWZWC12
fatcat:ceowcsdisjhhxgme5eqerbnila
« Previous
Showing results 1 — 15 out of 1,363 results