A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth 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
A bootstrapping framework for annotating and retrieving WWW images
Proceedings of the 12th annual ACM international conference on Multimedia
Formulating Semantic Image Annotation as a Supervised Learning Problem
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Learning the Semantics of Images by Using Unlabeled Samples
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Evaluating the impact of selection noise in community-based web search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Proceedings of the 18th international conference on World wide web
Proceedings of the ACM International Conference on Image and Video Retrieval
Image retrieval using Markov Random Fields and global image features
Proceedings of the ACM International Conference on Image and Video Retrieval
Large-scale music tag recommendation with explicit multiple attributes
Proceedings of the international conference on Multimedia
Automatic image search based on improved feature descriptors and decision tree
Integrated Computer-Aided Engineering
Knowledge propagation in large image databases using neighborhood information
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Automatic annotation of tagged content using predefined semantic concepts
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Annotation propagation in image databases using similarity graphs
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Structural image retrieval using automatic image annotation and region based inverted file
Journal of Visual Communication and Image Representation
Hi-index | 0.00 |
Automatic image annotation (AIA) has been a hot research topic in recent years since it can be used to support concept-based image retrieval. However, most existing AIA models depend heavily on the availability of a large number of labeled training samples, which require significant human labeling efforts. In this paper, we propose a novel learning framework which integrates text-based Bayesian model (TBM) and concept ontology to effectively expand the training set of each concept class without the need of additional human labeling efforts or collecting additional training images from other data sources. The basic idea lies in exploiting the text information from training set to provide additional effective annotations for training images so that training data for each concept class can be augmented. In this study we employ Bayesian Hierarchical Multinomial Mixture Models (BHMMMs) as our baseline AIA model. By combining additional annotations obtained from TBM into each concept class in the training phase, the performance of BHMMMs can be significantly improved on Corel image dataset with 263 testing concepts as compared to the state-of-the-art AIA models under the same experimental configurations.