Automatic image annotation by mining the web

Authors:
Zhiguo Gong;Qian Liu;Jingbai Zhang
Affiliations:
Faculty of Science and Technology, University of Macau, Macao, PRC;Faculty of Science and Technology, University of Macau, Macao, PRC;Faculty of Science and Technology, University of Macau, Macao, PRC
Venue:
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Year:
2006

Citing 11
Cited 1

Comparing images using color coherence vectors

MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
VisualSEEk: a fully automated content-based image query system

MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Giving meanings to WWW images

MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Learning-based linguistic indexing of pictures with 2--d MHMMs

Proceedings of the tenth ACM international conference on Multimedia
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
Modeling annotated data

Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Matching words and pictures

The Journal of Machine Learning Research
A bootstrapping approach to annotating large image collection

MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
A Novel Approach to Auto Image Annotation Based on Pairwise Constrained Clustering and Semi-Naïve Bayesian Model

MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
An implementation of web image search engines

ICADL'04 Proceedings of the 7th international Conference on Digital Libraries: international collaboration and cross-fertilization
CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines

IEEE Transactions on Circuits and Systems for Video Technology

The effectiveness of image features based on fractal image coding for image annotation

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic image annotation has been becoming an attractive research subject. Most current image annotation methods are based on training techniques. The major weaknesses of such solutions include limited annotation vocabulary and labor-intensive involvement. However, Web images possess a lot of texts, and rich annotation of samples is provided. Therefore, this report provides a novel image annotation method by mining the Web that term-image correlation is obtained from the Web not by learning. Without question, there are many noises in that relation, and some cleaning works are necessary. In the system, entropy weighting and image clustering technique are employed. Our experiment results show that our solution can achieve a satisfactory performance.