Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Learning and inferring a semantic space from user's relevance feedback for image retrieval
Proceedings of the tenth ACM international conference on Multimedia
eID: a system for exploration of image databases
Information Processing and Management: an International Journal
The Journal of Machine Learning Research
Visualization and User-Modeling for Browsing Personal Photo Libraries
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Proceedings of the 12th annual ACM international conference on Multimedia
Multimodal concept-dependent active learning for image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Multi-model similarity propagation and its application for web image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
Web image clustering by consistent utilization of visual features and surrounding texts
Proceedings of the 13th annual ACM international conference on Multimedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Learning nonparametric kernel matrices from pairwise constraints
Proceedings of the 24th international conference on Machine learning
A novel approach to enable semantic and visual image summarization for exploratory image search
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
JustClick: personalized image recommendation via exploratory search from large-scale Flickr images
IEEE Transactions on Circuits and Systems for Video Technology
Statistical modeling and conceptualization of natural images
Pattern Recognition
A novel approach for filtering junk images from google search results
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Hidden semantic concept discovery in region based image retrieval
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Multimedia
Scene Parsing Using Region-Based Generative Models
IEEE Transactions on Multimedia
Mining Multilevel Image Semantics via Hierarchical Classification
IEEE Transactions on Multimedia
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Mercer kernel-based clustering in feature space
IEEE Transactions on Neural Networks
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Automatic image annotation by using relevant keywords extracted from auxiliary text documents
Proceedings of the international workshop on Very-large-scale multimedia corpus, mining and retrieval
Efficient large-scale image data set exploration: visual concept network and image summarization
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
A novel facial expression database construction method based on web images
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Generating visual concept network from large-scale weakly-tagged images
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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The keyword-based Google Images search engine is now becoming very popular for online image search. Unfortunately, only the text terms that are explicitly or implicitly linked with the images are used for image indexing but the associated text terms may not have exact correspondence with the underlying image semantics, thus the keyword-based Google Images search engine may return large amounts of junk images which are irrelevant to the given keyword-based queries. Based on this observation, we have developed an interactive approach to filter out the junk images from keyword-based Google Images search results and our approach consists of the following major components. a) A kernel-based image clustering technique is developed to partition the returned images into multiple clusters and outliers. b) Hyperbolic visualization is incorporated to display large amounts of returned images according to their nonlinear visual similarity contexts, so that users can assess the relevance between the returned images and their real query intentions interactively and select one or multiple images to express their query intentions and personal preferences precisely. c) An incremental kernel learning algorithm is developed to translate the users' query intentions and personal preferences for updating the mixture-of-kernels and generating better hypotheses to achieve more accurate clustering of the returned images and filter out the junk images more effectively. Experiments on diverse keyword-based queries from Google Images search engine have obtained very positive results. Our junk image filtering system is released for public evaluation at: http://www.cs.uncc.edu/~jfan/google_demo/.