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DRM: dynamic region matching for image retrieval using probabilistic fuzzy matching and boosting feature selection

Rongrong Ji, Hongxun Yao, Dawei Liang
2007 Signal, Image and Video Processing  
This paper considers the semantic gap in content-based image retrieval from two aspects: (1) irrelevant visual contents (e.g. background) scatter the mapping from image to human perception; (2) unsupervised  ...  This paper proposes a novel region-based retrieval framework-dynamic region matching (DRM) to bridge the semantic gap. (1) To address the first issue, a probabilistic fuzzy region matching algorithm is  ...  FeatureBoost: dynamic feature selection based on AdaBoost for relevance feedback learning In relevance feedback, the variety of users' retrieval intention restricts the efficiency of RF learning based  ... 
doi:10.1007/s11760-007-0037-0 fatcat:mm3fhh7lj5fsbbvdkvg2zzzigi

Region-based Image Retrieval Using Probabilistic Feature Relevance Learning

Jing Peng, ByoungChul Ko, Hyeran Byun
2001 Pattern Analysis and Applications  
Region-Based Image Retrieval (RBIR), a specialisation of content-based image retrieval, is a promising and important research area.  ...  It is, therefore, imperative to develop effective mechanisms for interactive, region-based visual query in order to provide confident retrieval performance.  ...  Acknowledgement The authors would like to thank the anonymous reviewers for their valuable comments.  ... 
doi:10.1007/s100440170015 fatcat:jvkzgnhumbhqlhbt5nnlpqjuty

Relevance Feedback in CBIR [chapter]

Hongjiang Zhang, Zhong Su
2002 Visual and Multimedia Information Management  
A new focus in content-based image retrieval (CBIR) research is applying relevance feedback originally developed for text document retrieval, to improve the retrieval performance.  ...  We consider relevance feedback in CBIR a small sample-learning process in sparse image feature space. Almost all of the previously proposed methods fall well into such framework.  ...  By analysing the feature distribution of the segmented regions, a probability association between each segmented regions and annotated keywords is set up for labelled images by region-based relevance feedback  ... 
doi:10.1007/978-0-387-35592-4_3 fatcat:s56mbelgvzgvfcxhjlbnldkwma

Web Image Mining Based on Modeling Concept-Sensitive Salient Regions

Jing Liu, Qingshan Liu, Jinqiao Wang, Hanqing Lu, Songde Ma
2006 2006 IEEE International Conference on Multimedia and Expo  
In this paper, we propose a probabilistic model for web image mining, which is based on concept-sensitive salient regions without human intervene.  ...  With the help of a popular search engine, semantically relevant images are collected, and conceptsensitive salient regions are extracted automatically based on an attention model.  ...  Probabilistic Model for Image Semantic Content To get a Gaussian mixture model for concept-sensitive salient regions, we need training samples, i.e. semantically relevant regions.  ... 
doi:10.1109/icme.2006.262436 dblp:conf/icmcs/LiuLWLM06 fatcat:cvtpla5pxba2tmjycmzlz5bcfm

Population-Based Incremental Interactive Concept Learning for Image Retrieval by Stochastic String Segmentations

S. Ghebreab, C.C. Jaffe, A.W.M. Smeulders
2004 IEEE Transactions on Medical Imaging  
Index Terms-Content-based image retrieval, multifeature object description, population-based incremental learning, relevance feedback, visual concept learning.  ...  We propose a method for concept-based medical image retrieval that is a superset of existing semantic-based image retrieval methods.  ...  ACKNOWLEDGMENT The authors are thankful to the Lister Hill National Center for Biomedical Communications, NLM/NIH for providing NHANES II images from the National Center for Health Statistics.  ... 
doi:10.1109/tmi.2004.826942 pmid:15191142 fatcat:b5ykfyxgyzdkziaqqgyc7ny7ni

Region-Based Image Retrieval using Radial Basis Function Network

Kui Wu, Kim-hui Yap, Lap-pui Chau
2006 2006 IEEE International Conference on Multimedia and Expo  
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN).  ...  A new kernel function of RBFN is introduced for image similarity comparison under region-based representation.  ...  Since different regions in an image have unequal importance for computing image similarity, we propose a probabilistic region weight learning method to capture the relevance of the constituent regions  ... 
doi:10.1109/icme.2006.262896 dblp:conf/icmcs/WuYC06 fatcat:bavljarz6jcaxcur7qnaa6gyhm

Cross-Media Retrieval using Probabilistic Model of Automatic Image Annotation

Ying Xia, YunLong Wu, JiangFan Feng
2015 International Journal of Signal Processing, Image Processing and Pattern Recognition  
In this paper, we propose a kind of probabilistic model which may assign keywords to an un-annotated image automatically based on a training dataset of images.  ...  Furthermore, the feature vectors of text documents are generated by TF.IDF method and images' automatic annotation information is used to retrieve relevant text documents.  ...  Brezovan [17] present a system used in the medical domain for three tasks: image annotation, semantic based image retrieval and content based image retrieval. J. Y. Pan, H. J. Yang, C.  ... 
doi:10.14257/ijsip.2015.8.4.13 fatcat:6selth3jtfbv5gjptmqpbox3mu

Efficient search

Alexander G. Hauptmann, Jonathan J. Wang, Wei-Hao Lin, Jun Yang, Michael Christel
2008 Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08  
We introduce an interface for efficient video search that exploits the human ability to quickly scan visual content, after an automatic system has done its best to arrange the images in order of relevance  ...  The system will demonstrate several ways to rapidly scan images, change search queries, and employ different types of relevance feedback.  ...  Thus the system searches video for similar regions to ones specified by the user in a sample query image.  ... 
doi:10.1145/1386352.1386422 dblp:conf/civr/HauptmannWLYC08 fatcat:zrjpi3y7xnhkxk33hrh7ewt2qe

Ontological inference for image and video analysis

Christopher Town
2006 Machine Vision and Applications  
The first consists of a content based image retrieval system which allows users to search image databases using an ontological query language.  ...  Queries are parsed using a probabilistic grammar and Bayesian networks to map high level concepts onto low level image descriptors, thereby bridging the "semantic gap" between users and the retrieval system  ...  Acknowledgements The author would like to acknowledge financial support from AT&T Labs Research and the Royal Commission for the Exhibition of 1851.  ... 
doi:10.1007/s00138-006-0017-3 fatcat:hat7556tmzbctpebyvzx3xr4dy

Image Annotation Refinement Using Dynamic Weighted Voting Based on Mutual Information

Haiyu Song, Xiongfei Li, Pengjie Wang
2011 Journal of Software  
Automatic image annotation is a promising solution to narrow the semantic gap between low-level content and high-level semantic concept, which has been an active research area in the fields of image retrieval  ...  , pattern recognition, and machine learning.  ...  ACKNOWLEDGMENT We would like to express our grateful thanks to the faculty and students in Institute of Computer Graphics and Image Processing for their helping in experiment and evaluation.  ... 
doi:10.4304/jsw.6.11.2239-2246 fatcat:u62uugs4ebht7l5oblxofceuqe

Content-based image retrieval

Ritendra Datta, Jia Li, James Z. Wang
2005 Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval - MIR '05  
The last decade has witnessed great interest in research on content-based image retrieval.  ...  In this paper, we discuss some of the key contributions in the current decade related to image retrieval and automated image annotation, spanning 120 references.  ...  A framework for region-based image retrieval using region codebooks and learned region weights has been proposed in [49] .  ... 
doi:10.1145/1101826.1101866 dblp:conf/mir/DattaLW05 fatcat:puk37fqtbng77dwtjd7sjyz2xi

Clustering-based subspace SVM ensemble for relevance feedback learning

Rongrong Ji, Hongxun Yao, Jicheng Wang, Pengfei Xu, Xianming Liu
2008 2008 IEEE International Conference on Multimedia and Expo  
Finally, regression results of multiple SVMs are probabilistic assembled to give the final labeling prediction for test image.  ...  This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning.  ...  INTRODUCTION Content-based image retrieval (CBIR) aims at retrieving images based on their visual contents. It is a long-standing research hot spot over the past decade [1] .  ... 
doi:10.1109/icme.2008.4607661 dblp:conf/icmcs/JiYWXL08 fatcat:sy3pw3dwx5bszc6eyebbgn3elu

Review: Automatic Semantic Image Annotation

Shereen A. Hussein, Howida Youssry Abd El Naby, Aliaa A. A. Youssif
This paper aims to cover a review on different Models (MT, CRM, CSD-Prop, SVD-COS and CSD-SVD) for automating the process of image annotation as an intermediate step in image retrieval process using Corel  ...  Automated image annotation is creating a model capable of assigning terms to an image in order to describe its content.  ...  It associates one or more multiple concepts with objects and images therefor it is the professional way for content based image retrieval.  ... 
doi:10.24297/ijct.v15i12.4357 fatcat:i2ckwkzicbgnvfl6k3suy2bie4

Automatic Image Annotation with Relevance Feedback and Latent Semantic Analysis [chapter]

Donn Morrison, Stéphane Marchand-Maillet, Eric Bruno
2008 Lecture Notes in Computer Science  
Latent semantic analysis (LSA), a method originally designed for text retrieval, is applied to an image/session matrix where relevance feedback examples are collected from a large number of artificial  ...  We demonstrate how automatic annotation of images can be implemented on partially annotated databases by learning imageconcept relationships from positive examples via inter-query learning.  ...  Introduction Content-based image retrieval is burdened by a dichotomy between user-desired highlevel concepts and the low-level descriptions that retrieval systems are capable of indexing.  ... 
doi:10.1007/978-3-540-79860-6_6 fatcat:l5y7ly5jhrdxflr4r6v4dwhkqm

Modeling, classifying and annotating weakly annotated images using Bayesian network

Sabine Barrat, Salvatore Tabbone
2010 Journal of Visual Communication and Image Representation  
In this paper, we propose a probabilistic graphical model to represent weakly annotated images.  ...  We consider an image as weakly annotated if the number of keywords defined for it is less than the maximum number defined in the ground truth.  ...  The second approach, called ''content-based image retrieval" [32] is a younger field.  ... 
doi:10.1016/j.jvcir.2010.02.010 fatcat:zivdw7pabbg5hko4flmpcojtie
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