Fast nearest neighbor retrieval for bregman divergences
Proceedings of the 25th international conference on Machine learning
Exploring multimedia in a keyword space
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Image retrieval using query by contextual example
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Foundations and Trends in Information Retrieval
Inferring semantic concepts from community-contributed images and noisy tags
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Similarity search on Bregman divergence: towards non-metric indexing
Proceedings of the VLDB Endowment
Algorithms for reducing the semantic gap in image retrieval systems
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Combining visual features and text data for medical image retrieval using latent semantic kernels
Proceedings of the international conference on Multimedia information retrieval
Relevance feature mapping for content-based image retrieval
Proceedings of the Tenth International Workshop on Multimedia Data Mining
NMF-based multimodal image indexing for querying by visual example
Proceedings of the ACM International Conference on Image and Video Retrieval
IPSILON: incremental parsing for semantic indexing of latent concepts
IEEE Transactions on Image Processing
A new approach to cross-modal multimedia retrieval
Proceedings of the international conference on Multimedia
Shiatsu: semantic-based hierarchical automatic tagging of videos by segmentation using cuts
Proceedings of the 3rd international workshop on Automated information extraction in media production
A novel method for image retrieval using relevance feedback and unsupervised clustering
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
Connected component in feature space to capture high level semantics in CBIR
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
Image retrieval with semantic sketches
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part I
Learning pit pattern concepts for gastroenterological training
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Relevance feature mapping for content-based multimedia information retrieval
Pattern Recognition
Using manual and automated annotations to search images by semantic similarity
Multimedia Tools and Applications
A Probabilistic Model to Combine Tags and Acoustic Similarity for Music Retrieval
ACM Transactions on Information Systems (TOIS)
Content-Based retrieval in endomicroscopy: toward an efficient smart atlas for clinical diagnosis
MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Effective heterogeneous similarity measure with nearest neighbors for cross-media retrieval
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Halfway through the semantic gap: Prosemantic features for image retrieval
Information Sciences: an International Journal
The effectiveness of image features based on fractal image coding for image annotation
Expert Systems with Applications: An International Journal
Query-by-example approach towards on-demand multidimensional analysis
International Journal of Business Intelligence and Data Mining
PRiSMA: searching images in parallel
Proceedings of the 20th ACM international conference on Multimedia
Attributes for classifier feedback
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Scene recognition on the semantic manifold
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
SHIATSU: tagging and retrieving videos without worries
Multimedia Tools and Applications
A semantic model for cross-modal and multi-modal retrieval
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Parallel field alignment for cross media retrieval
Proceedings of the 21st ACM international conference on Multimedia
Querying for video events by semantic signatures from few examples
Proceedings of the 21st ACM international conference on Multimedia
Robust image retrieval with hidden classes
Computer Vision and Image Understanding
A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics
International Journal of Computer Vision
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A combination of query-by-visual-example (QBVE) and semantic retrieval (SR), denoted as query-by-semantic-example (QBSE), is proposed. Images are labeled with respect to a vocabulary of visual concepts, as is usual in SR. Each image is then represented by a vector, referred to as a semantic multinomial, of posterior concept probabilities. 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. QBSE is shown to have two main properties of interest, one mostly practical and the other philosophical. From a practical standpoint, because it inherits the generalization ability of SR inside the space of known visual concepts (referred to as the semantic space) but performs much better outside of it, QBSE produces retrieval systems that are more accurate than what was previously possible. Philosophically, because it allows a direct comparison of visual and semantic representations under a common query paradigm, QBSE enables the design of experiments that explicitly test the value of semantic representations for image retrieval. An implementation of QBSE under the minimum probability of error (MPE) retrieval framework, previously applied with success to both QBVE and SR, is proposed, and used to demonstrate the two properties. In particular, an extensive objective comparison of QBSE with QBVE is presented, showing that the former significantly outperforms the latter both inside and outside the semantic space. By carefully controlling the structure of the semantic space, it is also shown that this improvement can only be attributed to the semantic nature of the representation on which QBSE is based.