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
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Correlated Label Propagation with Application to Multi-label Learning
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation refinement using random walk with restarts
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Image annotation via graph learning
Pattern Recognition
A New Baseline for Image Annotation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
SIAM Journal on Imaging Sciences
The segmented and annotated IAPR TC-12 benchmark
Computer Vision and Image Understanding
Semantics-preserving bag-of-words models and applications
IEEE Transactions on Image Processing
Multi-label boosting for image annotation by structural grouping sparsity
Proceedings of the international conference on Multimedia
Image annotation by sparse logistic regression
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
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
Image annotation by kNN-sparse graph-based label propagation over noisily tagged web images
ACM Transactions on Intelligent Systems and Technology (TIST)
Multi-layer group sparse coding -- For concurrent image classification and annotation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning Visual Contexts for Image Annotation From Flickr Groups
IEEE Transactions on Multimedia
Contextual Kernel and Spectral Methods for Learning the Semantics of Images
IEEE Transactions on Image Processing
Spectral learning of latent semantics for action recognition
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
| Hi-index | 0.00 |
This paper presents a new semantic sparse recoding method to generate more descriptive and robust representation of visual content for image annotation. Although the visual bag-of-words (BOW) representation has been reported to achieve promising results in image annotation, its visual codebook is completely learnt from low-level visual features using quantization techniques and thus the so-called semantic gap remains unbridgeable. To handle such challenging issue, we utilize both the annotations of training images and the predicted annotations of test images to improve the original visual BOW representation. This is further formulated as a sparse coding problem so that the noise issue induced by the inaccurate quantization of visual features can also be handled to some extent. By developing an efficient sparse coding algorithm, we successfully generate a new visual BOW representation for image annotation. Since such sparse coding has actually incorporated the high-level semantic information into the original visual codebook, we thus consider it as semantic sparse recoding of the visual content. Although the predicted annotations of test images are also used as inputs by the traditional image annotation refinement, we focus on the visual BOW representation refinement for image annotation in this paper. The experimental results on two benchmark datasets show the superior performance of our semantic sparse recoding method in image annotation.