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Image Retrieval based on VA-File and Multi-Resolution BOW

Wang Lipin, Pu Juncheng
2015 Applied Mathematics & Information Sciences  
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

Wang Lipin, Pu Juncheng
2015 Applied Mathematics & Information Sciences  
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]

Stephen O'Hara, Bruce A. Draper
2011 arXiv   pre-print
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

Mohammed O. Assayony et. al.
2018 International Journal of Computing and Digital Systems  
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

Joan Sosa-Garcia, Francesca Odone
2015 Proceedings of the 10th International Conference on Computer Vision Theory and Applications  
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

Xinchao Li, Martha Larson, Alan Hanjalic
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
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

Felsia Thompson, Jeyakumar M.K
2017 International Journal of Engineering and Technology  
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

Chih-Fan Chen, Yu-Chiang Frank Wang
2011 Proceedings of the 19th ACM international conference on Multimedia - MM '11  
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

Jianlong Wu, Zhouchen Lin, Hongbin Zha
2015 Proceedings of the 2015 ACM on International Conference on Multimodal Interaction - ICMI '15  
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

Fan Liu, Sai Yang, Yuhua Ding, Feng Xu
2019 Multimedia tools and applications  
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

Liujuan Cao, Rongrong Ji, Yue Gao, Yi Yang, Qi Tian
2012 2012 IEEE Conference on Computer Vision and Pattern Recognition  
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

Meng-Jiun Chiou, Toshihiko Yamasaki, Aizawa Kiyoharu
2015 Proceedings of the ITE Annual Convention  
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

Zhouhui Lian, Afzal Godil, Xianfang Sun, Hai Zhang
2010 2010 IEEE International Conference on Image Processing  
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]

Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro
2016 arXiv   pre-print
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

Hanli Wang, Yun Shen, Lei Wang, Kuangtian Zhufeng, Wei Wang, Cheng Cheng
2012 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings  
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
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