SVD and signal processing: algorithms, applications and architectures
SVD and signal processing: algorithms, applications and architectures
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Entropy-based subspace clustering for mining numerical data
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
End-User Searching Challenges Indexing Practices inthe Digital Newspaper Photo Archive
Information Retrieval
Browse and Search Patterns in a Digital Image Database
Information Retrieval
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Journal of Machine Learning Research
Regularizing translation models for better automatic image annotation
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Automatic image annotation and retrieval using subspace clustering algorithm
Proceedings of the 2nd ACM international workshop on Multimedia databases
Narrowing the semantic gap - improved text-based web document retrieval using visual features
IEEE Transactions on Multimedia
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
A framework for a video analysis tool for suspicious event detection
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
A framework for a video analysis tool for suspicious event detection
Multimedia Tools and Applications
Feature selection based-on genetic algorithm for image annotation
Knowledge-Based Systems
Improved Resulted Word Counts Optimizer for Automatic Image Annotation Problem
Fundamenta Informaticae - Advances in Artificial Intelligence and Applications
PhotoMap - automatic spatiotemporal annotation for mobile photos
W2GIS'07 Proceedings of the 7th international conference on Web and wireless geographical information systems
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A semantic approach and a web tool for contextual annotation of photos using camera phones
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Improving image annotations using wordnet
MIS'05 Proceedings of the 11th international conference on Advances in Multimedia Information Systems
Improved Resulted Word Counts Optimizer for Automatic Image Annotation Problem
Fundamenta Informaticae - Advances in Artificial Intelligence and Applications
SHIATSU: tagging and retrieving videos without worries
Multimedia Tools and Applications
Using Hilbert scan on statistical color space partitioning
Computers and Electrical Engineering
Human computation: Image metadata acquisition based on a single-player annotation game
International Journal of Human-Computer Studies
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The development of technology generates huge amounts of non-textual information, such as images. An efficient image annotation and retrieval system is highly desired. Clustering algorithms make it possible to represent visual features of images with finite symbols. Based on this, many statistical models, which analyze correspondence between visual features and words and discover hidden semantics, have been published. These models improve the annotation and retrieval of large image databases. However, image data usually have a large number of dimensions. Traditional clustering algorithms assign equal weights to these dimensions, and become confounded in the process of dealing with these dimensions. In this paper, we propose weighted feature selection algorithm as a solution to this problem. For a given cluster, we determine relevant features based on histogram analysis and assign greater weight to relevant features as compared to less relevant features. We have implemented various different models to link visual tokens with keywords based on the clustering results of K-means algorithm with weighted feature selection and without feature selection, and evaluated performance using precision, recall and correspondence accuracy using benchmark dataset. The results show that weighted feature selection is better than traditional ones for automatic image annotation and retrieval.