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A Three-Dimensional Representation Scheme for Indexing and Querying in Iconic Image Databases [chapter]

Jae-Woo Chang
1999 Database Semantics  
In order to accelerate image searching, we also design an efficient retrieval method using a signature file technique.  ...  In multimedia information retrieval applications, content-based image retrieval is essential for retrieving relevant multimedia documents.  ...  As shown in Figure 15.8(b) , we obtain only one qualifying image to satisfy the query since we use a small database with 100 real interior design images.  ... 
doi:10.1007/978-0-387-35561-0_15 fatcat:vvxuvrvgf5cffpok73hu6vvjou

A retrieval pattern-based inter-query learning approach for content-based image retrieval

Adam D. Gilbert, Ran Chang, Xiaojun Qi
2010 2010 IEEE International Conference on Image Processing  
User's relevance feedback is utilized for updating high-level semantic features of the query image and each database image.  ...  This paper presents a retrieval pattern-based inter-query learning approach for image retrieval with relevance feedback.  ...  Randomly select 10% of the database images from each semantic category as training query images. 3.  ... 
doi:10.1109/icip.2010.5654156 dblp:conf/icip/GilbertCQ10 fatcat:tog3ro5ufzegtputdgkrid6xwq

Complementary relevance feedback-based content-based image retrieval

Zhongmiao Xiao, Xiaojun Qi
2013 Multimedia tools and applications  
the query in a single retrieval session.  ...  Specifically, we construct an adaptive semantic repository in long-term learning to store retrieval patterns of historical query sessions.  ...  Acknowledgments This material is based upon work supported in part by the National Science Foundation under Grant No. 0850825.  ... 
doi:10.1007/s11042-013-1693-4 fatcat:ndwovewc2fhd7muj32f4px345i

Block-based long-term content-based image retrieval using multiple features

Zhongmiao Xiao, Xiaojun Qi
2013 2013 IEEE International Conference on Multimedia and Expo (ICME)  
The history is compactly stored in a semantic feature matrix and efficiently represented as semantic features of the images.  ...  This paper proposes a novel content-based image retrieval technique, which integrates block-based visual features and user's query concept-based semantic features.  ...  The size of this semantic feature matrix is initially set to be N×50, where N is the total number of images in the database and 50 is an initial estimate of the number of semantic concepts in the database  ... 
doi:10.1109/icme.2013.6607471 dblp:conf/icmcs/XiaoQ13 fatcat:uxnmbesr5nbuxnmm3ug2rgb24i

A hybrid approach to multimedia database systems through integration of semantics and media-based search [chapter]

Wen-Syan Li, K. Selçuk Candan, Kyoji Hirata, Yoshinori Hara
1997 Lecture Notes in Computer Science  
SEMCOG (SEMantics and COGnition-based image retrieval) is a multimedia database system based on this hybrid architecture.  ...  With the increasing interest in multimedia, researchers across various disciplines, in particular, the database community and image processing community, have teamed up to conduct research in building  ...  Image data is semantically richer than the traditional data forms stored in databases since it contains both semantics and visual meanings to the viewers.  ... 
doi:10.1007/3-540-63343-x_47 fatcat:jwolssbqhjewfopeecddjjoe5a

SEMCOG

Wen-Syan Li, K. Selçuk Candan, Kyoji Hirata
1997 Proceedings of the 1997 ACM symposium on Applied computing - SAC '97  
Image retrieval is a key issue for many image database applications. Existing approaches include browsing and keyword, semantics, and cognition-based query processing.  ...  Example queries are used to illustrate the image retrieval process in SEMCOG.  ...  His current research interests include multimedia data modeling, multimedia databases, image/video retrieval, digital libraries, heterogeneous database, and object-relational database systems. K.  ... 
doi:10.1145/331697.331727 dblp:conf/sac/LiCH97 fatcat:52jiky55czcencjr66cxehbl7e

Semantic clustering and querying on heterogeneous features for visual data

Gholamhosein Sheikholeslami, Wendy Chang, Aidong Zhang
1998 Proceedings of the sixth ACM international conference on Multimedia - MULTIMEDIA '98  
In this paper, we present a semanticsbased clustering approach, termed SemQuery, to support visual queries on heterogeneous features of images.  ...  Each semantic image cluster contains a set of subclusters that are represented by the heterogeneous features that the images contain.  ...  However, such an approach will result in a linear search to all images in the database, causing ineciency in querying.  ... 
doi:10.1145/290747.290749 dblp:conf/mm/SheikholeslamiCZ98 fatcat:5a3a3uw7ovgsbl2bnt5s6yge2m

A Scalable Graph-Based Semi-Supervised Ranking System for Content-Based Image Retrieval

Xiaojun Qi, Ran Chang
2013 International Journal of Multimedia Data Engineering and Management  
Active learning is applied to build a dynamic feedback log to extract semantic features of images. Two-layer manifold graphs are then built in both low-level visual and high-level semantic spaces.  ...  Several graphs are constructed at the second layer using images in their respective cluster formed around each anchor image.  ...  The more images in the database, the more possible semantic concepts are.  ... 
doi:10.4018/ijmdem.2013100102 fatcat:c4b76naaejhyhcwxghskmk7lte

SEMCOG

Wen-Syan Li, K. Selçuk Candan, Kyoji Hirata, Yoshinori Hara
1997 Proceedings of the 1997 ACM SIGMOD international conference on Management of data - SIGMOD '97  
Introduction Image retrieval is a key issue in many image database applications.  ...  The queries are posed in the way of specifying image objects and their layouts using a visual query interface, IFQ (In Frame Query), rather than complicated multimedia database query languages.  ... 
doi:10.1145/253260.253384 dblp:conf/sigmod/LiCHH97 fatcat:dvjijuygunag5awymlsp7yx5te

SEMCOG

Wen-Syan Li, K. Selçuk Candan, Kyoji Hirata, Yoshinori Hara
1997 SIGMOD record  
Introduction Image retrieval is a key issue in many image database applications.  ...  The queries are posed in the way of specifying image objects and their layouts using a visual query interface, IFQ (In Frame Query), rather than complicated multimedia database query languages.  ... 
doi:10.1145/253262.253384 fatcat:2li7si23kzb4haba3sxxjooqbi

A study of query by semantic example

Nikhil Rasiwasia, Nuno Vasconcelos
2008 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
In recent years, query-by-semantic-example (QBSE) has become a popular approach to do content based image retrieval [20, 23, 18] .  ...  QBSE extends the well established query-by-example retrieval paradigm to the semantic domain.  ...  Similarity matching in semantic space is also illustrated in Fig. 2 , which depicts a query and the two closest database matches.  ... 
doi:10.1109/cvprw.2008.4563046 dblp:conf/cvpr/RasiwasiaV08a fatcat:bfyewza4rjbzhklwaliy5hdbqa

Learning from Relevance Feedback Sessions using a K-Nearest-Neighbor-Based Semantic Repository

Matthew Ro, Ran Chang, Xiaojun Qi
2007 Multimedia and Expo, 2007 IEEE International Conference on  
The dot product measures the semantic similarity between the query and each database image.  ...  This repository semantically relates each database image to a set of training images chosen from all semantic categories.  ...  from each semantic category in the image database.  ... 
doi:10.1109/icme.2007.4285070 dblp:conf/icmcs/RoyalCQ07 fatcat:dmf6zfenp5fcplj5wc4ghpnphu

An effective noise-resilient long-term semantic learning approach to content-based image retrieval

Jacob Linenthal, Xiaojun Qi
2008 Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing  
Specifically, it uses a statistical memory learning method based on the user's feedback to extract additional high-level semantic information between query and database images.  ...  These two measures are seamlessly combined to compute the overall similarity between query and database images.  ...  A semantic matrix of size M×M, where M is the total number of images in the database, stores the similarity measure for each pair of images returned in each query session.  ... 
doi:10.1109/icassp.2008.4517834 dblp:conf/icassp/LinenthalQ08 fatcat:jwrkqyp7bvhjtemmktbqsfm7vi

Bridging the Gap: Query by Semantic Example

Nikhil Rasiwasia, P.J. Moreno, N. Vasconcelos
2007 IEEE transactions on multimedia  
Retrieval is based on the query-by-example paradigm: the user provides a query image, for which 1) a semantic multinomial is computed and 2) matched to those in the database.  ...  Index Terms-Content-based image retrieval, Gaussian mixtures, image similarity, multiple instance learning, query by example, semantic retrieval, semantic space.  ...  Barnard for providing the Corel dataset used in [14] . Finally, they would like to thank the reviewers for insightful comments that helped to improve the paper.  ... 
doi:10.1109/tmm.2007.900138 fatcat:6g2tyue26vfnxndcsoavvbohze

A fuzzy statistical correlation-based approach to content-based image retrieval

Xiaojun Qi, Ran Chang
2008 2008 IEEE International Conference on Multimedia and Expo  
They are also used to more accurately estimate the semantic similarity between the query image and database images.  ...  The overall similarity score between query and database images is computed by combining both low-level visual and high-level semantic similarity measures.  ...  These two sets of experiments demonstrate that the correlation-based long-term semantic relation does help in learning the semantic similarity between query image and each database image since both of  ... 
doi:10.1109/icme.2008.4607672 dblp:conf/icmcs/QiC08 fatcat:la5detivqbh3lg4gckpxtdjyfe
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