On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
A Markov Random Field Model-Based Approach to Image Interpretation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
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
The Journal of Machine Learning Research
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Tagging English text with a probabilistic model
Computational Linguistics
Image Categorization by Learning and Reasoning with Regions
The Journal of Machine Learning Research
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Proceedings of the 12th annual ACM international conference on Multimedia
On the detection of semantic concepts at TRECVID
Proceedings of the 12th annual ACM international conference on Multimedia
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Shallow parsing with conditional random fields
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
Large Margin Methods for Structured and Interdependent Output Variables
The Journal of Machine Learning Research
Region based image annotation through multiple-instance learning
Proceedings of the 13th annual ACM international conference on Multimedia
Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
2D Conditional Random Fields for Web information extraction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Peekaboom: a game for locating objects in images
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A hybrid framework for detecting the semantics of concepts and context
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Probabilistic spatial context models for scene content understanding
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Support vector random fields for spatial classification
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Semi-supervised learning for image annotation based on conditional random fields
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Image classification by a two-dimensional hidden Markov model
IEEE Transactions on Signal Processing
Leveraging probabilistic season and location context models for scene understanding
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Semantic object classes in video: A high-definition ground truth database
Pattern Recognition Letters
Labelling Image Regions Using Wavelet Features and Spatial Prototypes
SAMT '08 Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
SemanGist: A Local Semantic Image Representation
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Multiple-Instance Active Learning for Image Categorization
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Label to region by bi-layer sparsity priors
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Using visual context and region semantics for high-level concept detection
IEEE Transactions on Multimedia - Special issue on integration of context and content
Local-driven semi-supervised learning with multi-label
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Hidden-concept driven image decomposition towards semi-supervised multi-label image annotation
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Efficient large-scale image annotation by probabilistic collaborative multi-label propagation
Proceedings of the international conference on Multimedia
Image segmentation with patch-pair density priors
Proceedings of the international conference on Multimedia
Fuzzy based contextual cueing for region level annotation
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
An energy-based model for region-labeling
Computer Vision and Image Understanding
Region-based annotation of digital photographs
CCIW'11 Proceedings of the Third international conference on Computational color imaging
Image label completion by pursuing contextual decomposability
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Combining image-level and segment-level models for automatic annotation
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Label-to-region with continuity-biased bi-layer sparsity priors
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Improving image retrieval by using spatial relations
Multimedia Tools and Applications
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In this paper we conduct a relatively complete study on how to exploit spatial context constraints for automated image region annotation. We present a straight forward method to regularize the segmented regions into 2D lattice layout, so that simple grid-structure graphical models can be employed to characterize the spatial dependencies. We show how to represent the spatial context constraints in various graphical models and also present the related learning and inference algorithms. Different from most of the existing work, we specifically investigate how to combine the classification performance of discriminative learning and the representation capability of graphical models. To reliably evaluate the proposed approaches, we create a moderate scale image set with region-level ground truth. The experimental results show that (i) spatial context constraints indeed help for accurate region annotation, (ii) the approaches combining the merits of discriminative learning and context constraints perform best, (iii) image retrieval can benefit from accurate region-level annotation.