Markov random field modeling in image analysis
Markov random field modeling in image analysis
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
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
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Hidden Markov models for automatic annotation and content-based retrieval of images and video
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Joint visual-text modeling for automatic retrieval of multimedia documents
Proceedings of the 13th annual ACM international conference on Multimedia
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
A linear-algebraic technique with an application in semantic image retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Logistic regression of generic codebooks for semantic image retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Exploring Flickr's related tags for semantic annotation of web images
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
An annotation rule extraction algorithm for image retrieval
Pattern Recognition Letters
Labeling images by integrating sparse multiple distance learning and semantic context modeling
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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This paper proposes a formal framework for image and video retrieval using discrete Markov random fields (MRF). The training dataset consists of images with keywords (regions are not labeled). The model is built using a discrete vocabulary of vector quantized region or point features generated from the training images. Since performance is dependent on the size of the vocabulary, a large vocabulary of a couple of million visterms is used. Such large vocabularies cannot be generated by conventional clustering algorithms so hierarchical k-means is used to generate it. Unlike many previous techniques, our MRF based model doesn't require an explicit annotation step for retrieval. The model directly ranks all test images according to the posterior probability of an image given a query. Traditionally, most models are trained by maximizing likelihood - instead this model is trained by maximizing average precision. Image and video retrieval experiments are performed on two standard datasets (a Corel dataset and a TRECVID3 dataset) which consist of 4,500 images and about 44,100 keyframes respectively. The results show that based on a large visual vocabulary the model runs extremely fast on even very large datasets while having comparable retrieval performance to the best performing (continuous feature) models.